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21. The computer program product of claim 20 , wherein the rescanning is performed by a user computer system.

21. The computer program product of claim 20 , wherein the rescanning is performed by a user computer system. 23. The computer program product of claim 21 , wherein the messages that are rescanned are in an inbox on the email server.

11. A computer system configured to generate an Availability Management Framework (AMF) configuration for providing services and protecting the services against resource failure, wherein the AMF configuration is an instance of an AMF sub-profile that defines a set of AMF elements to be used to model resources and the services, and is generated from an instance of an Entity Types File (ETF) sub-profile, which is called an ETF model, and an instance of a Configuration Requirements (CR) sub-profile, which is called a CR model, each of the AMF sub-profile, the ETF sub-profile and the CR sub-profile being with a specialization of a pre-defined Unified Modeling Language (UML) meta-model, the computer system comprising: a memory storing: the ETF model, which defines a set of ETF prototypes of the ETF model that describe the resources provided by vendors; and the CR model, which defines a set of CR elements of the CR model that specify configuration requirements; and a processor coupled to the memory, the processor configured to: receive the ETF model and the CR model, and apply a set of transformation rules, which are pre-defined for the ETF sub-profile, the CR sub-profile and the AMF sub-profile, to transform the ETF model and the CR model into an AMF model as the AMF configuration, wherein the CR model is organized as a first hierarchy of the CR elements, the ETF model is organized as a second hierarchy of the ETF prototypes, and one or more levels of the first hierarchy are missing in the second hierarchy, the processor is further configured to transform a selected subset of the ETF prototypes of the ETF model that satisfy the configuration requirements into a collection of the AMF elements organized as a hierarchy with the one or more levels missing, and build the one or more missing levels from the collection of the AMF elements based on relationships between the one or more missing levels and existing levels of the first and the second hierarchies.

11. A computer system configured to generate an Availability Management Framework (AMF) configuration for providing services and protecting the services against resource failure, wherein the AMF configuration is an instance of an AMF sub-profile that defines a set of AMF elements to be used to model resources and the services, and is generated from an instance of an Entity Types File (ETF) sub-profile, which is called an ETF model, and an instance of a Configuration Requirements (CR) sub-profile, which is called a CR model, each of the AMF sub-profile, the ETF sub-profile and the CR sub-profile being with a specialization of a pre-defined Unified Modeling Language (UML) meta-model, the computer system comprising: a memory storing: the ETF model, which defines a set of ETF prototypes of the ETF model that describe the resources provided by vendors; and the CR model, which defines a set of CR elements of the CR model that specify configuration requirements; and a processor coupled to the memory, the processor configured to: receive the ETF model and the CR model, and apply a set of transformation rules, which are pre-defined for the ETF sub-profile, the CR sub-profile and the AMF sub-profile, to transform the ETF model and the CR model into an AMF model as the AMF configuration, wherein the CR model is organized as a first hierarchy of the CR elements, the ETF model is organized as a second hierarchy of the ETF prototypes, and one or more levels of the first hierarchy are missing in the second hierarchy, the processor is further configured to transform a selected subset of the ETF prototypes of the ETF model that satisfy the configuration requirements into a collection of the AMF elements organized as a hierarchy with the one or more levels missing, and build the one or more missing levels from the collection of the AMF elements based on relationships between the one or more missing levels and existing levels of the first and the second hierarchies. 12. The computer system of claim 11 , wherein the computer system is further configured to: from the ETF model, select the ETF prototypes that satisfy the configuration requirements to form the selected subset of the ETF prototypes; create a collection of AMF Types that describe characteristics of the AMF elements based on the selected subset of the ETF prototypes and the CR model; and create the subset of the AMF elements based on the collection of AMF Types and the CR model to form the AMF configuration.

6. The method of claim 4 , including comparing data indicative of a plurality of search results to data indicative of a second aspect of the user context to determine a plurality of relevance scores associated with the plurality of search results, the second aspect of the user context including data indicative of at least one task in which the user is engaged out of a plurality of possible user tasks.

6. The method of claim 4 , including comparing data indicative of a plurality of search results to data indicative of a second aspect of the user context to determine a plurality of relevance scores associated with the plurality of search results, the second aspect of the user context including data indicative of at least one task in which the user is engaged out of a plurality of possible user tasks. 8. The method of claim 6 , wherein the first aspect of the user context includes the second aspect of the user context.

17. An information retrieval system, comprising: an information retrieval apparatus for retrieving a name including input characters from a database; and a server coupled to the information retrieval apparatus via a network, wherein: the information retrieval apparatus comprises: an input unit for inputting characters; a database for storing the name, an attribute word associated with the name, and a degree of relevance indicating a degree of relevance between the name and the attribute word; a name retrieval unit for retrieving a name including the input characters from the database to output the retrieved name as a candidate name; an attribute word generating unit for extracting an attribute word associated with the candidate name output from the name retrieval unit from the database; an output unit for displaying the attribute word extracted by the attribute word generating unit and the candidate name from the name retrieval unit; a communication unit for communicating with the server; and an updating unit for degree of relevance for updating the degree of relevance stored in the database with a degree of relevance received from the server; the attribute word generating unit is configured to: obtain a degree of relevance of the candidate name associated with the attribute word from the database with respect to a combination of the extracted attribute words; calculate a degree of independency indicating a degree of difference between the extracted attribute words; calculate a degree of coverage indicating an extent to which the combination of the extracted attribute words covers of the candidate names; and calculate a degree of equality indicating uniformity of a number of corresponding candidate names for each attribute word; the attribute word generating unit comprises a first score calculating unit for calculating a score of the combination of the attribute words based on at least one of the calculated degree of independency, the calculated degree of coverage and the calculated degree of equality; and the attribute word generating unit outputs the combinations of the attribute words to the output unit in a descending order of the score.

17. An information retrieval system, comprising: an information retrieval apparatus for retrieving a name including input characters from a database; and a server coupled to the information retrieval apparatus via a network, wherein: the information retrieval apparatus comprises: an input unit for inputting characters; a database for storing the name, an attribute word associated with the name, and a degree of relevance indicating a degree of relevance between the name and the attribute word; a name retrieval unit for retrieving a name including the input characters from the database to output the retrieved name as a candidate name; an attribute word generating unit for extracting an attribute word associated with the candidate name output from the name retrieval unit from the database; an output unit for displaying the attribute word extracted by the attribute word generating unit and the candidate name from the name retrieval unit; a communication unit for communicating with the server; and an updating unit for degree of relevance for updating the degree of relevance stored in the database with a degree of relevance received from the server; the attribute word generating unit is configured to: obtain a degree of relevance of the candidate name associated with the attribute word from the database with respect to a combination of the extracted attribute words; calculate a degree of independency indicating a degree of difference between the extracted attribute words; calculate a degree of coverage indicating an extent to which the combination of the extracted attribute words covers of the candidate names; and calculate a degree of equality indicating uniformity of a number of corresponding candidate names for each attribute word; the attribute word generating unit comprises a first score calculating unit for calculating a score of the combination of the attribute words based on at least one of the calculated degree of independency, the calculated degree of coverage and the calculated degree of equality; and the attribute word generating unit outputs the combinations of the attribute words to the output unit in a descending order of the score. 18. The information retrieval system according to claim 17 , wherein the attribute word stored in the database comprises a morpheme constituting a part of the candidate name.

8. A system for validating access to a first element within a group of related elements, comprising: a network that is configured to provide access to web pages; and a computing device coupled to the network, the computing device including an application that is configured to: associate a security context with each element within the group of related elements; verify access to the first element when the security context associated with the first element permits access to the first element; invalidate access to the first element when the security context associated with the first element does not permit access to the first element; navigate a markup page associated with the first element; and modify the security context associated with a second element in response to navigating the markup page.

8. A system for validating access to a first element within a group of related elements, comprising: a network that is configured to provide access to web pages; and a computing device coupled to the network, the computing device including an application that is configured to: associate a security context with each element within the group of related elements; verify access to the first element when the security context associated with the first element permits access to the first element; invalidate access to the first element when the security context associated with the first element does not permit access to the first element; navigate a markup page associated with the first element; and modify the security context associated with a second element in response to navigating the markup page. 9. The system of claim 8 , wherein the markup page is navigated from a first domain to a second domain.

17. A computerized apparatus having a processor, the processor being adapted to perform the steps of: obtaining an identifier of an operations sequence comprising one or more operations, each operation representing a user interaction with an element of a Graphical User Interface (GUI) for operating a computing device; wherein said obtaining the identifier comprises obtaining a vocal command of the user and extracting the identifier from the vocal command; obtaining the operations sequence, wherein obtaining comprises searching a repository of operations sequences using the identifier to obtain the operations sequence, wherein the repository of operation sequences comprises operations sequences defined based on a previous execution of one or more operations by another computing device other than the computing device on behalf of another user other than the user; and automatically executing the operations sequence or portion thereof on the computing device, wherein for each of the one or more operations said automatically executing comprising: determining a required element for user interaction therewith which the operation represents based on a layout of a GUI displayed during previous execution of the operation by another computing device, whereby unique and persistent identification of an element interacted therewith on behalf of another user while defining the operations sequence is obtainable; obtaining and analyzing a layout of a GUI being displayed on a display screen of the computing device to determine whether the required element is available therein; and, responsive to determination that the required element is available, automatically executing the operation by mimicking user interaction therewith.

17. A computerized apparatus having a processor, the processor being adapted to perform the steps of: obtaining an identifier of an operations sequence comprising one or more operations, each operation representing a user interaction with an element of a Graphical User Interface (GUI) for operating a computing device; wherein said obtaining the identifier comprises obtaining a vocal command of the user and extracting the identifier from the vocal command; obtaining the operations sequence, wherein obtaining comprises searching a repository of operations sequences using the identifier to obtain the operations sequence, wherein the repository of operation sequences comprises operations sequences defined based on a previous execution of one or more operations by another computing device other than the computing device on behalf of another user other than the user; and automatically executing the operations sequence or portion thereof on the computing device, wherein for each of the one or more operations said automatically executing comprising: determining a required element for user interaction therewith which the operation represents based on a layout of a GUI displayed during previous execution of the operation by another computing device, whereby unique and persistent identification of an element interacted therewith on behalf of another user while defining the operations sequence is obtainable; obtaining and analyzing a layout of a GUI being displayed on a display screen of the computing device to determine whether the required element is available therein; and, responsive to determination that the required element is available, automatically executing the operation by mimicking user interaction therewith. 21. The computerized apparatus of claim 17 , wherein said processor is further adapted to perform the steps of: responsive to a determination that execution of the operations sequence cannot be completed automatically, prompting a user of the computing device to complete execution of the operations sequence; monitoring operations of the user to determine an intermediary operations sequence; and storing the intermediary operations sequence for future use.

1. A method for processing and producing email documents, the method comprising: receiving, by a processor, information organizing a first plurality of email documents into a plurality of document groups; generating, by the processor, a graphical user interface for reviewing a document group from the plurality of document groups, the document group including a second plurality of email documents from the first plurality of email documents that are organized into the document group, wherein the second plurality of email documents represent an email thread, and wherein the graphical user interface comprises a first section displaying the document group and a second section to receive a plurality of review content to associate with each of the second plurality of email documents or to associate with each of the email documents of other document groups from the plurality of document groups based on a selection from the second section of the graphical user interface; receiving, by the processor, the plurality of review content comprising one or more annotations provided by a user of the graphical user interface that are applicable to the document group; associating, by the processor, the plurality of review content with the document group; for each review content of the plurality of review content: determining, by the processor, a propagation for the review content to the second plurality of emails, and propagating, by the processor, the review content to the second plurality of email documents based on the determined propagation for the review content, wherein the review content is propagated to each email document in the second plurality of email documents, or the review content is propagated to a subset of email documents in the second plurality of email documents, and wherein one or more of the email documents of the second plurality of email documents comprises at least one multiply annotated email document that is associated with the plurality of the review content and is annotated based on an aggregation of the plurality of review content; and producing, by the processor, a third plurality of email documents from the first plurality of email documents in response to one or more queries related to the one or more annotations in the review content that has been propagated, the third plurality of email documents including at least one email document from the second plurality of email documents in the document group.

1. A method for processing and producing email documents, the method comprising: receiving, by a processor, information organizing a first plurality of email documents into a plurality of document groups; generating, by the processor, a graphical user interface for reviewing a document group from the plurality of document groups, the document group including a second plurality of email documents from the first plurality of email documents that are organized into the document group, wherein the second plurality of email documents represent an email thread, and wherein the graphical user interface comprises a first section displaying the document group and a second section to receive a plurality of review content to associate with each of the second plurality of email documents or to associate with each of the email documents of other document groups from the plurality of document groups based on a selection from the second section of the graphical user interface; receiving, by the processor, the plurality of review content comprising one or more annotations provided by a user of the graphical user interface that are applicable to the document group; associating, by the processor, the plurality of review content with the document group; for each review content of the plurality of review content: determining, by the processor, a propagation for the review content to the second plurality of emails, and propagating, by the processor, the review content to the second plurality of email documents based on the determined propagation for the review content, wherein the review content is propagated to each email document in the second plurality of email documents, or the review content is propagated to a subset of email documents in the second plurality of email documents, and wherein one or more of the email documents of the second plurality of email documents comprises at least one multiply annotated email document that is associated with the plurality of the review content and is annotated based on an aggregation of the plurality of review content; and producing, by the processor, a third plurality of email documents from the first plurality of email documents in response to one or more queries related to the one or more annotations in the review content that has been propagated, the third plurality of email documents including at least one email document from the second plurality of email documents in the document group. 13. The method of claim 1 wherein receiving the information organizing the first plurality of email documents into the plurality of document groups includes organizing the first plurality of email documents in accordance with meta information associated with the first plurality of email documents.

2. The method of claim 1 , wherein the electronic representation of the conversation includes an audio file.

2. The method of claim 1 , wherein the electronic representation of the conversation includes an audio file. 3. The method of claim 2 , further comprising receiving an indication that the first portion of the electronic representation of the conversation begins at a first time of the audio file and ends a second time of the audio file.

1. A system for aligning content, the system comprising: an electronic data store configured to store: an electronic book comprising: a plurality of paragraphs of body text, and matter other than body text, wherein the matter other than body text comprises text within at least front matter and back matter; and an audiobook that is a companion to the electronic book; and a physical computing device in communication with the electronic data store, the physical computing device configured to: generate a textual transcription of the audiobook by applying a speech-to-text recognition routine on the audiobook; identify a portion of the textual transcription that includes text also included in a paragraph of the electronic book; determine a level of correlation between words in the paragraph of the electronic book and words in the portion of the textual transcription; determine that the level of correlation satisfies a threshold value; in response to determining that the level of correlation satisfies the threshold value, identify the paragraph of the electronic book as body text; identify a first portion of the electronic book that does not satisfy the threshold value with respect to the textual transcription; determine that the first portion of the electronic book that does not satisfy the threshold value is front matter based at least in part on a determination that the first portion of the electronic book that does not satisfy the threshold value appears within the electronic book prior to an earliest portion of the electronic book for which a corresponding portion of the audiobook is identified; identify a second portion of the electronic book that does not satisfy the threshold value with respect to the textual transcription; determine that the second portion of the electronic book that does not satisfy the threshold value is back matter based at least in part on a determination that the second portion of the electronic book that does not satisfy the threshold value appears within the electronic book after a last portion of the electronic book for which a corresponding portion of the audiobook is identified; and generate content synchronization information that identifies (a) portions of the audiobook that correspond to the paragraphs of the body text and (b) further identifies the matter other than body text in the electronic book, wherein the content synchronization information indicates that the matter other than body text in the electronic book, including the first portion and second portion of the electronic book, does not correspond to any portion of the audiobook, wherein the content synchronization information indicates that the paragraph, excluding the matter other than body text, should be presented in synchronization with a portion of the audiobook from which the corresponding portion of the textual transcription was generated.

1. A system for aligning content, the system comprising: an electronic data store configured to store: an electronic book comprising: a plurality of paragraphs of body text, and matter other than body text, wherein the matter other than body text comprises text within at least front matter and back matter; and an audiobook that is a companion to the electronic book; and a physical computing device in communication with the electronic data store, the physical computing device configured to: generate a textual transcription of the audiobook by applying a speech-to-text recognition routine on the audiobook; identify a portion of the textual transcription that includes text also included in a paragraph of the electronic book; determine a level of correlation between words in the paragraph of the electronic book and words in the portion of the textual transcription; determine that the level of correlation satisfies a threshold value; in response to determining that the level of correlation satisfies the threshold value, identify the paragraph of the electronic book as body text; identify a first portion of the electronic book that does not satisfy the threshold value with respect to the textual transcription; determine that the first portion of the electronic book that does not satisfy the threshold value is front matter based at least in part on a determination that the first portion of the electronic book that does not satisfy the threshold value appears within the electronic book prior to an earliest portion of the electronic book for which a corresponding portion of the audiobook is identified; identify a second portion of the electronic book that does not satisfy the threshold value with respect to the textual transcription; determine that the second portion of the electronic book that does not satisfy the threshold value is back matter based at least in part on a determination that the second portion of the electronic book that does not satisfy the threshold value appears within the electronic book after a last portion of the electronic book for which a corresponding portion of the audiobook is identified; and generate content synchronization information that identifies (a) portions of the audiobook that correspond to the paragraphs of the body text and (b) further identifies the matter other than body text in the electronic book, wherein the content synchronization information indicates that the matter other than body text in the electronic book, including the first portion and second portion of the electronic book, does not correspond to any portion of the audiobook, wherein the content synchronization information indicates that the paragraph, excluding the matter other than body text, should be presented in synchronization with a portion of the audiobook from which the corresponding portion of the textual transcription was generated. 2. The system of claim 1 , wherein the physical computing device is further configured to provide the content synchronization information to a separate computing device.

2. The method of claim 1 wherein defining TC-related policies further includes defining general and dynamic subject and object attributes to specify TC-related policies.

2. The method of claim 1 wherein defining TC-related policies further includes defining general and dynamic subject and object attributes to specify TC-related policies. 3. The method of claim 2 wherein extending the SELinux policy model further includes extending the identity-role-type policy model (user:role:type) of SELinux to include user:profile:role:type:system profile reflecting TC requirements.

44. A process implemented across a network having one or more publishing sites correspondingly associated with at least one publishing entity, each of the publishing sites comprising at least one publisher page having publishing content that is displayable to any user of the publishing site, and at least one available ad space, the process comprising: providing at least one processor that is programmed to perform the steps of: storing a plurality of anonymous profiles that are associated with a plurality of users; receiving a catalog file from an advertiser entity across the network, the catalog file comprising a plurality of asset records, wherein each of the asset records comprises a plurality of fields correspondingly associated with an asset; receiving from the advertiser entity one or more action objectives associated with the assets; assigning bids for the received action objectives associated with the assets, wherein the assigned bids correspond to a price corresponding to an accomplishment of a corresponding action objective; analyzing one or more of the fields that correspond to each of the asset records; storing the analyzed asset records; automatically producing ads corresponding to the analyzed asset records, wherein the produced ads include the analyzed fields; statistically matching a user at a user terminal with one of the stored plurality of anonymous profiles, wherein the matching is at least partially based upon known information about the user, wherein the known information comprises any of location, gender, age, interests, purchases, usage patterns, or other prior actions by the user; predicting a response to the ads by the user, wherein the prediction is at least partially based on the matched stored profile and at least one of the analyzed fields associated with the automatically produced ads and any of the analyzed publishing content and the analyzed ads received from the advertising entities, and wherein said prediction comprises a predicted impression revenue; determining one or more of the best stored ads based on the predicted impression revenue and an observed effective impression revenue of the stored ads, wherein the processor is programmed to track a past number of impressions and resulting actions and to estimate the observed effective impression revenue of the stored ads; and wherein the processor is programmed to apply a blending function B to the predicted impression revenue p, and to the number of impressions i and number of resulting actions a: B ( p,i,a ) wherein for each impression i and the resulting action a, the observed effective impression revenue of the stored ads is are tested for statistical significance against the predicted effective impression revenue p, wherein when the statistical significance exceeds a predetermined threshold, the processor is programmed to use the observed effective impression revenue of the stored ads as the determined effective impression revenue of the stored ads; otherwise, the processor is programmed to use the predicted effective impression revenue of the stored ads; and sending one or more of the automatically produced ads for presentation to the user, based upon the prediction.

44. A process implemented across a network having one or more publishing sites correspondingly associated with at least one publishing entity, each of the publishing sites comprising at least one publisher page having publishing content that is displayable to any user of the publishing site, and at least one available ad space, the process comprising: providing at least one processor that is programmed to perform the steps of: storing a plurality of anonymous profiles that are associated with a plurality of users; receiving a catalog file from an advertiser entity across the network, the catalog file comprising a plurality of asset records, wherein each of the asset records comprises a plurality of fields correspondingly associated with an asset; receiving from the advertiser entity one or more action objectives associated with the assets; assigning bids for the received action objectives associated with the assets, wherein the assigned bids correspond to a price corresponding to an accomplishment of a corresponding action objective; analyzing one or more of the fields that correspond to each of the asset records; storing the analyzed asset records; automatically producing ads corresponding to the analyzed asset records, wherein the produced ads include the analyzed fields; statistically matching a user at a user terminal with one of the stored plurality of anonymous profiles, wherein the matching is at least partially based upon known information about the user, wherein the known information comprises any of location, gender, age, interests, purchases, usage patterns, or other prior actions by the user; predicting a response to the ads by the user, wherein the prediction is at least partially based on the matched stored profile and at least one of the analyzed fields associated with the automatically produced ads and any of the analyzed publishing content and the analyzed ads received from the advertising entities, and wherein said prediction comprises a predicted impression revenue; determining one or more of the best stored ads based on the predicted impression revenue and an observed effective impression revenue of the stored ads, wherein the processor is programmed to track a past number of impressions and resulting actions and to estimate the observed effective impression revenue of the stored ads; and wherein the processor is programmed to apply a blending function B to the predicted impression revenue p, and to the number of impressions i and number of resulting actions a: B ( p,i,a ) wherein for each impression i and the resulting action a, the observed effective impression revenue of the stored ads is are tested for statistical significance against the predicted effective impression revenue p, wherein when the statistical significance exceeds a predetermined threshold, the processor is programmed to use the observed effective impression revenue of the stored ads as the determined effective impression revenue of the stored ads; otherwise, the processor is programmed to use the predicted effective impression revenue of the stored ads; and sending one or more of the automatically produced ads for presentation to the user, based upon the prediction. 48. The process of claim 44 , wherein the bids correspond to any of cost per click (CPC), cost per impression (CPM), ad-based cost per action (CPA) bids, and commission-based CPA bids.

6. An information search method for searching through a database having a plurality of document data each having a unique document ID added thereto, by use of a computer having a storage device, the method comprising the steps of: storing each of the plurality of document data in the storage device in a form of a structural tree starting from a root node by parsing; storing in the storage device occurrence information for each word in each of the plurality of document data when each of the document data is a parse tree with the root node for bundling a plurality of sentences, the occurrence information containing a document ID of the document data including the word, a first order that indicates a sequence number of the word originating from a root node in a structural tree, and a second order that indicates a reverse sequence number of the word originating from a terminal node to the root node in the structural tree, wherein the first order sequence number decreases in value as position proximity of the word to the root node increases, and wherein the second order reverse sequence number decreases in value as position proximity of the word to the terminal node increases; receiving information on at least two words to be searched for; reading from the storage device the occurrence information on each of the words received; comparing occurrence information on a first word among the received words with occurrence information on a second word among the received words; and searching out a document ID of one of the above two kinds of occurrence information which has the same document ID as the other occurrence information, the first order smaller than the other occurrence information, and the second order larger than the other occurrence information.

6. An information search method for searching through a database having a plurality of document data each having a unique document ID added thereto, by use of a computer having a storage device, the method comprising the steps of: storing each of the plurality of document data in the storage device in a form of a structural tree starting from a root node by parsing; storing in the storage device occurrence information for each word in each of the plurality of document data when each of the document data is a parse tree with the root node for bundling a plurality of sentences, the occurrence information containing a document ID of the document data including the word, a first order that indicates a sequence number of the word originating from a root node in a structural tree, and a second order that indicates a reverse sequence number of the word originating from a terminal node to the root node in the structural tree, wherein the first order sequence number decreases in value as position proximity of the word to the root node increases, and wherein the second order reverse sequence number decreases in value as position proximity of the word to the terminal node increases; receiving information on at least two words to be searched for; reading from the storage device the occurrence information on each of the words received; comparing occurrence information on a first word among the received words with occurrence information on a second word among the received words; and searching out a document ID of one of the above two kinds of occurrence information which has the same document ID as the other occurrence information, the first order smaller than the other occurrence information, and the second order larger than the other occurrence information. 7. The information search method according to claim 6 , wherein the occurrence information is sorted and listed in descending order of document frequency for each word ID.

1. A method performed by a computer system for combining multiple classifiers, comprising: for each classifier, setting to zero multipliers associated with data elements that were not used to construct the classifier; and constructing a combined classifier by setting its multiplier values to a weighted average of the multipliers associated with the multiple classifiers wherein a combined support vector machine associated with a classifier receives an input, x, and computes a classification for the received input as ĝ(x)=ψ(Σ i=1 l {circumflex over (α)} i y i K(x i ,x)+{circumflex over (b)}).

1. A method performed by a computer system for combining multiple classifiers, comprising: for each classifier, setting to zero multipliers associated with data elements that were not used to construct the classifier; and constructing a combined classifier by setting its multiplier values to a weighted average of the multipliers associated with the multiple classifiers wherein a combined support vector machine associated with a classifier receives an input, x, and computes a classification for the received input as ĝ(x)=ψ(Σ i=1 l {circumflex over (α)} i y i K(x i ,x)+{circumflex over (b)}). 3. The method of claim 1 wherein the weight for each of the multiplier values associated with a classifier is computed based on a margin of a support vector machine associated with the classifier.

33. The method of claim 24 , wherein the search engine comprises: a number of pipelined engines, each having a data input to selectively receive the normalized un-encoded filtered input string, and each having a control input to receive a corresponding trigger signal generated by the parser.

33. The method of claim 24 , wherein the search engine comprises: a number of pipelined engines, each having a data input to selectively receive the normalized un-encoded filtered input string, and each having a control input to receive a corresponding trigger signal generated by the parser. 34. The method of claim 33 , wherein the pipelined engines comprise: a deterministic finite automaton (DFA) engine; and a non-deterministic finite automaton (NFA) engine.

8. A computer implemented method for querying a markup language document having hierarchical information including a parent node and descendent nodes related to the parent node, comprising: storing, in a data source, a markup language document; retrieving the markup language document; identifying and extracting information from the retrieved markup language document in response to a query by consulting a mapping specification containing information for locating the parent node, and if the parent node satisfies the query, storing the parent node in a first table; and locating the descendent nodes by consulting the mapping specification if the parent node satisfies the query and storing said descendent nodes in a second table.

8. A computer implemented method for querying a markup language document having hierarchical information including a parent node and descendent nodes related to the parent node, comprising: storing, in a data source, a markup language document; retrieving the markup language document; identifying and extracting information from the retrieved markup language document in response to a query by consulting a mapping specification containing information for locating the parent node, and if the parent node satisfies the query, storing the parent node in a first table; and locating the descendent nodes by consulting the mapping specification if the parent node satisfies the query and storing said descendent nodes in a second table. 13. The computer implemented method of claims 8 , wherein the identifying includes identifying repeating elements in the markup language document.

1. A method of recognizing speech by measuring confidence levels of respective frames, the method comprising: obtaining frequency features of a received speech signal for the respective frames having a predetermined length; calculating a keyword model-based likelihood and a filler model-based likelihood for each of the frames; calculating confidence scores based on the two types of likelihoods for each of the frames; transforming the confidence scores by applying transform functions of clusters, which include the confidence scores or are close to the confidence scores, to the confidence scores; and deciding whether the received speech signal corresponds to a keyword or a non-keyword based on a combination of confidence scores of each frame, wherein the frames constitute a subword, and wherein the deciding comprises the operation of calculating skewness of a distribution of the confidence scores and correcting the confidence scores through an operation of subtracting a result, which is acquired by multiplying the calculated skewness by a constant, from the confidence scores.

1. A method of recognizing speech by measuring confidence levels of respective frames, the method comprising: obtaining frequency features of a received speech signal for the respective frames having a predetermined length; calculating a keyword model-based likelihood and a filler model-based likelihood for each of the frames; calculating confidence scores based on the two types of likelihoods for each of the frames; transforming the confidence scores by applying transform functions of clusters, which include the confidence scores or are close to the confidence scores, to the confidence scores; and deciding whether the received speech signal corresponds to a keyword or a non-keyword based on a combination of confidence scores of each frame, wherein the frames constitute a subword, and wherein the deciding comprises the operation of calculating skewness of a distribution of the confidence scores and correcting the confidence scores through an operation of subtracting a result, which is acquired by multiplying the calculated skewness by a constant, from the confidence scores. 5. The method as claimed in claim 1 , wherein the calculation of the keyword comprises the operation of calculating the keyword model-based likelihood or the filler model-based likelihood as a result of the feature extraction from each of the frames acquired by dividing the speech signal by a predetermined size.

1. A computer-implemented method of collaborative design for merging a first modeled object with a second modeled object wherein the first and second modeled objects are modified copies of an initial modeled object, wherein the first modeled object, the second modeled object and the initial modeled object are CAD three-dimensional modeled objects defined respectively by an initial graph (A), a first graph (B) and a second graph (B′), wherein the initial graph (A), the first graph (B) and the second graph (B′) are boundary representation graphs or history graphs, wherein the method comprises: providing the initial modeled object; providing a respective copy of the initial modeled object to each of a first user and a second user, with at least one processor: performing, by the first user, a design modification on the copy of the initial modeled object respective to the first user, thereby providing the first modeled object, performing, by the second user, a design modification on the copy of the initial modeled object respective to the second user, the design modification performed by the second user being different from the design modification performed by the first user, thereby providing the second modeled object, computing a first double push-out graph rewriting rule and a second double push-out graph rewriting rule, the first double push-out graph rewriting rule and the second double push-out graph rewriting rule corresponding respectively to a transformation of the initial graph (A) into the first graph (B) and the second graph (B′), wherein the first double push-out graph rewriting rule specifies a first part (L) from the initial graph (A) which is to be replaced when transforming the initial graph (A) into the first graph (B), a first replacement (R) to replace the first part (L), a first interface (G) between the first part (L) and the first replacement (R), first morphisms from the first interface (G) to the first part (L) and to the first replacement (R) respectively, and wherein the second double push-out graph rewriting rule specifies a second part (L′) from the initial graph (A) which is to be replaced when transforming the initial graph (A) into the second graph (B′), a second replacement (R′) to replace the second part (L′), a second interface (G′) between the second part (L′) and the second replacement (R′), second morphisms from the second interface (G′) to the second part (L′) and to the second replacement (R′) respectively; assembling the first rewriting rule and the second rewriting rule to determine and provide a third double push-out graph rewriting rule, wherein the third double push-out graph rewriting rule specifies an assembled part ({tilde over (L)}) which is an assembly of the first part (L) and the second part (L′), an assembled replacement ({tilde over (R)}) which is an assembly of the first replacement (R) and the second replacement (R′), an assembled interface ({tilde over (G)}) which is an assembly of the first interface (G) and the second interface (G′), assembled morphisms from the assembled interface ({tilde over (G)}) to the assembled part ({tilde over (L)}) and the assembled replacement ({tilde over (R)}) respectively, wherein an assembly of elements of the first and second rewriting rules consists, for each element, of a gathering of constituents of the element of the first rewriting rule with constituents of the element of the second rewriting rule; computing a merged graph (Ã) by applying the third double push-out graph rewriting rule to the initial graph (A), wherein the merged graph is translated in a merged modeled object.

1. A computer-implemented method of collaborative design for merging a first modeled object with a second modeled object wherein the first and second modeled objects are modified copies of an initial modeled object, wherein the first modeled object, the second modeled object and the initial modeled object are CAD three-dimensional modeled objects defined respectively by an initial graph (A), a first graph (B) and a second graph (B′), wherein the initial graph (A), the first graph (B) and the second graph (B′) are boundary representation graphs or history graphs, wherein the method comprises: providing the initial modeled object; providing a respective copy of the initial modeled object to each of a first user and a second user, with at least one processor: performing, by the first user, a design modification on the copy of the initial modeled object respective to the first user, thereby providing the first modeled object, performing, by the second user, a design modification on the copy of the initial modeled object respective to the second user, the design modification performed by the second user being different from the design modification performed by the first user, thereby providing the second modeled object, computing a first double push-out graph rewriting rule and a second double push-out graph rewriting rule, the first double push-out graph rewriting rule and the second double push-out graph rewriting rule corresponding respectively to a transformation of the initial graph (A) into the first graph (B) and the second graph (B′), wherein the first double push-out graph rewriting rule specifies a first part (L) from the initial graph (A) which is to be replaced when transforming the initial graph (A) into the first graph (B), a first replacement (R) to replace the first part (L), a first interface (G) between the first part (L) and the first replacement (R), first morphisms from the first interface (G) to the first part (L) and to the first replacement (R) respectively, and wherein the second double push-out graph rewriting rule specifies a second part (L′) from the initial graph (A) which is to be replaced when transforming the initial graph (A) into the second graph (B′), a second replacement (R′) to replace the second part (L′), a second interface (G′) between the second part (L′) and the second replacement (R′), second morphisms from the second interface (G′) to the second part (L′) and to the second replacement (R′) respectively; assembling the first rewriting rule and the second rewriting rule to determine and provide a third double push-out graph rewriting rule, wherein the third double push-out graph rewriting rule specifies an assembled part ({tilde over (L)}) which is an assembly of the first part (L) and the second part (L′), an assembled replacement ({tilde over (R)}) which is an assembly of the first replacement (R) and the second replacement (R′), an assembled interface ({tilde over (G)}) which is an assembly of the first interface (G) and the second interface (G′), assembled morphisms from the assembled interface ({tilde over (G)}) to the assembled part ({tilde over (L)}) and the assembled replacement ({tilde over (R)}) respectively, wherein an assembly of elements of the first and second rewriting rules consists, for each element, of a gathering of constituents of the element of the first rewriting rule with constituents of the element of the second rewriting rule; computing a merged graph (Ã) by applying the third double push-out graph rewriting rule to the initial graph (A), wherein the merged graph is translated in a merged modeled object. 2. The method of claim 1 , wherein the computing of a first double push-out graph rewriting rule and a second double push-out graph rewriting rule comprises: determining: a first common part between the initial graph and the first graph, and a second common part between the initial graph and the second graph determining: a first subtraction between the first graph and the first common part, a second subtraction between the second graph and the second common part, a third subtraction between the initial graph and the first common part, and a fourth subtraction between the initial graph and the second common part, determining: first end nodes which are nodes of the first common part missing from arcs of the first subtraction, second end nodes which are nodes of the second common part missing from arcs of the second subtraction, third end nodes which are nodes of the first common part missing from arcs of the third subtraction, and fourth end nodes which are nodes of the second common part missing from arcs of the fourth subtraction computing: the first interface as a union between the first end nodes and the third end nodes, the second interface as a union between the second end nodes and the fourth end nodes, the first part as a union between the first interface, the third subtraction, and the third end nodes, the second part as a union between the second interface, the fourth subtraction, and the fourth end nodes, the first replacement as a union between the first interface, the first subtraction, and the first end nodes, and the second replacement as a union between the second interface, the second subtraction, and the second end nodes.

5. The method as claimed in claim 4 , wherein processing logic is generated by a XSL/T engine using a compiler XSL/T document, the processing logic including an XSL/T template comprising logic for one of: explicitly excluding all of the additional elements of the second interface definition; and explicitly including all of the elements of the second interface definition that are not the additional elements of the second interface definition.

5. The method as claimed in claim 4 , wherein processing logic is generated by a XSL/T engine using a compiler XSL/T document, the processing logic including an XSL/T template comprising logic for one of: explicitly excluding all of the additional elements of the second interface definition; and explicitly including all of the elements of the second interface definition that are not the additional elements of the second interface definition. 6. The method as claimed in claim 5 , wherein explicitly excluding all of the additional elements of the second interface definition comprises: adding a default XSL/T template to the XSL/T document that copies an unmarked element and processes all elements of the unmarked element; adding a XSL/T template to the XSL/T document that copies an element marked for processing and selectively processes contained elements of the element marked for processing that are to be included; and adding a XSL/T template to the XSL/T document to avoid the use of the default XSL/T template for elements marked for deletion.

1. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving geotagged audio signals that correspond to environmental audio recorded by multiple mobile devices in multiple geographic locations, receiving an audio signal that corresponds to an utterance recorded by a particular mobile device, determining a particular geographic location associated with the particular mobile device, generating a noise model for the particular geographic location using a subset of the geotagged audio signals, and performing noise compensation on the audio signal that corresponds to the utterance using the noise model that has been generated for the particular geographic location.

1. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving geotagged audio signals that correspond to environmental audio recorded by multiple mobile devices in multiple geographic locations, receiving an audio signal that corresponds to an utterance recorded by a particular mobile device, determining a particular geographic location associated with the particular mobile device, generating a noise model for the particular geographic location using a subset of the geotagged audio signals, and performing noise compensation on the audio signal that corresponds to the utterance using the noise model that has been generated for the particular geographic location. 14. The system of claim 1 , wherein the operations further comprise: processing the received geotagged audio signals to exclude portions of the environmental audio that include voices of users of the multiple mobile devices.

1. A method comprising: presenting a map including a viewport showing a first location; receiving a first indication that a user is interacting with the map, including one or more first panning, scrolling, repositioning, or zooming interactions, to enable one or more intermediate locations to be visible in the viewport, without submitting a query for any of the intermediate locations; receiving a second indication that the user is continuing to interact with the map, including one or more second panning, scrolling, repositioning, or zooming interactions, to enable a location of interest to be visible in the viewport; determining, by one or more processors, that the user has arrived at the location of interest, the location of interest being visible in the viewport as a result of the second panning, scrolling, repositioning, or zooming interactions, the determining based at least in part on evaluating the first and second interactions; based on determining that the user has arrived at the location of interest, automatically submitting a query for the location of interest; receiving query results responsive to the query; and presenting the query results along with the viewport showing the location of interest.

1. A method comprising: presenting a map including a viewport showing a first location; receiving a first indication that a user is interacting with the map, including one or more first panning, scrolling, repositioning, or zooming interactions, to enable one or more intermediate locations to be visible in the viewport, without submitting a query for any of the intermediate locations; receiving a second indication that the user is continuing to interact with the map, including one or more second panning, scrolling, repositioning, or zooming interactions, to enable a location of interest to be visible in the viewport; determining, by one or more processors, that the user has arrived at the location of interest, the location of interest being visible in the viewport as a result of the second panning, scrolling, repositioning, or zooming interactions, the determining based at least in part on evaluating the first and second interactions; based on determining that the user has arrived at the location of interest, automatically submitting a query for the location of interest; receiving query results responsive to the query; and presenting the query results along with the viewport showing the location of interest. 14. The method of claim 1 where determining that the user has arrived further includes one or more of determining if movement in the map ends at a conclusion of a long sweep motion, or determining if a ballistic scroll has occurred, where either of the aforementioned conditions are indicative of the user not arriving.

11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, at an Internet search system, a search query; receiving multiple search results, each of the search results identifying an Internet resource indexed by the search system that satisfies the query; determining that the search query matches a name of a user that submitted the search query; providing, in response to the search query, a ranking of one or more of the search results and a personal knowledge panel comprising one or more items of user-provided information about the user, wherein the personal knowledge panel includes multiple input fields for updating the user-provided information of the knowledge panel; receiving updated user information that was provided using the input fields of the personal knowledge panel; and associating the updated user information with an account of the user.

11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, at an Internet search system, a search query; receiving multiple search results, each of the search results identifying an Internet resource indexed by the search system that satisfies the query; determining that the search query matches a name of a user that submitted the search query; providing, in response to the search query, a ranking of one or more of the search results and a personal knowledge panel comprising one or more items of user-provided information about the user, wherein the personal knowledge panel includes multiple input fields for updating the user-provided information of the knowledge panel; receiving updated user information that was provided using the input fields of the personal knowledge panel; and associating the updated user information with an account of the user. 15. The system of claim 11 , wherein the operations further comprise providing a different ranking of one or more search results based on the updated user information without further input from the user.

16. A system for analyzing effectiveness and accuracy of a file detection rule, comprising: computing hardware, including a processor, a data storage device, and input/output devices including a network interface device and a graphical user interface; the data storage device containing a set of unknown files to be analyzed for a presence of malware; instructions executable on the computing hardware and stored in a non-transitory storage medium that, when executed, cause the computing hardware to implement: a check module configured to apply a detection rule to each of the files in the set of unknown files, wherein the detection rule defines criteria for distinguishing files having at least one characteristic of interest from other files lacking the at least one characteristic of interest; wherein as a result of application of the detection rule, the check module is configured to produce a result set that contains files detected from among the set of unknown files as having the at least one characteristic of interest and excludes the other files lacking the at least one characteristic of interest; an analysis module configured to compare each file from the result set to at least one file from a set of known files having the at least one characteristic of interest to produce a first measure of similarity, and to at least one file from a set of known files lacking the characteristic of interest to produce a second measure of similarity; wherein in response to the first measure of similarity exceeding a first similarity threshold, the detection rule is deemed effective; and wherein in response to the second measure of similarity exceeding a second similarity threshold, the detection rule is deemed inaccurate.

16. A system for analyzing effectiveness and accuracy of a file detection rule, comprising: computing hardware, including a processor, a data storage device, and input/output devices including a network interface device and a graphical user interface; the data storage device containing a set of unknown files to be analyzed for a presence of malware; instructions executable on the computing hardware and stored in a non-transitory storage medium that, when executed, cause the computing hardware to implement: a check module configured to apply a detection rule to each of the files in the set of unknown files, wherein the detection rule defines criteria for distinguishing files having at least one characteristic of interest from other files lacking the at least one characteristic of interest; wherein as a result of application of the detection rule, the check module is configured to produce a result set that contains files detected from among the set of unknown files as having the at least one characteristic of interest and excludes the other files lacking the at least one characteristic of interest; an analysis module configured to compare each file from the result set to at least one file from a set of known files having the at least one characteristic of interest to produce a first measure of similarity, and to at least one file from a set of known files lacking the characteristic of interest to produce a second measure of similarity; wherein in response to the first measure of similarity exceeding a first similarity threshold, the detection rule is deemed effective; and wherein in response to the second measure of similarity exceeding a second similarity threshold, the detection rule is deemed inaccurate. 18. The system of claim 16 , wherein the instructions cause the computing hardware to implement a clustering module configured to separate an available set of files into subsets that include the known files having the at least one characteristic of interest, the known files lacking the at least one characteristic of interest, and the set of unknown files.

26. A mobile device, comprising: means for receiving an indication of activation of one of a plurality of search switches having associated therewith a subset of characters; a storage device configured to store a set of content objects; means for identifying a set of names associated with the set of content objects stored in the storage device responsive to the means for activating the one of the plurality of search switches, the set of names including one or more names each having in a first character position one or more characters in the subset of characters; responsive to the set of names including only one name having in the first character position the one or more characters in the subset of characters, means for displaying the one name; responsive to the set of names including more than the one name having in the first character position the one or more characters in the subset of characters, means for displaying in a first display position at least one place holder character associated with the one or more characters in the subset of characters included in the set of names; and means for repeatedly receiving the indication of activation for subsequent character positions, means for identifying, and means for displaying in subsequent display positions further ones of the at least one place holder character for subsequent indications of activations of any of the plurality of search switches until the means for displaying displays only the one name; wherein the at least one place holder character represents plural names and a count of unresolved characters in the set of names.

26. A mobile device, comprising: means for receiving an indication of activation of one of a plurality of search switches having associated therewith a subset of characters; a storage device configured to store a set of content objects; means for identifying a set of names associated with the set of content objects stored in the storage device responsive to the means for activating the one of the plurality of search switches, the set of names including one or more names each having in a first character position one or more characters in the subset of characters; responsive to the set of names including only one name having in the first character position the one or more characters in the subset of characters, means for displaying the one name; responsive to the set of names including more than the one name having in the first character position the one or more characters in the subset of characters, means for displaying in a first display position at least one place holder character associated with the one or more characters in the subset of characters included in the set of names; and means for repeatedly receiving the indication of activation for subsequent character positions, means for identifying, and means for displaying in subsequent display positions further ones of the at least one place holder character for subsequent indications of activations of any of the plurality of search switches until the means for displaying displays only the one name; wherein the at least one place holder character represents plural names and a count of unresolved characters in the set of names. 27. The mobile device of claim 26 further comprising: means for transmitting the indication of activation of the one of the plurality of search switches from a remote player including the plurality of search switches coupled to the storage device through a network; means for transmitting the set of names from the storage device to the remote player; means for indicating the activation of a control switch to select a displayed name on the remote player; and means for transmitting a content object corresponding to the selected displayed name from the storage device to the remote player responsive to receiving an indication of the activating of the control switch.

17. A computer-implemented method for programmatically interfacing each of two or more affiliate merchant devices including at least a first merchant device and a second merchant device, with a payment application to reduce a transaction time for consumer-facing operations in a retail environment, the method comprising: receiving, from the first merchant device, during a first transaction, a first name and a last name of a consumer and an associated payment method; subsequent to the first transaction, receiving, during a second transaction, with the second merchant device, identity information, the second merchant device being different than the first merchant device; determining that the consumer previously interacted with an affiliate merchant device, the affiliate merchant device being the first merchant device subsequent to the determination that the consumer previously interacted with the affiliate merchant device, matching the identity information received during the second transaction to the first and last name of the consumer received during the first transaction; and identifying, based on the match of the identity information received during the second transaction to the first and last name of the consumer received during the first transaction, a consumer profile associated with the payment method, the consumer profile associated with the email suggestor system; identify, from the consumer profile, an associated email address associated with the consumer profile; providing, during the second transaction, an interface to a third-party payment application; and causing, during the second transaction, display of the email address associated with the consumer profile associated with the payment method configured to reduce the transaction time, subsequent to the identification of the associated email address associated with the consumer profile.

17. A computer-implemented method for programmatically interfacing each of two or more affiliate merchant devices including at least a first merchant device and a second merchant device, with a payment application to reduce a transaction time for consumer-facing operations in a retail environment, the method comprising: receiving, from the first merchant device, during a first transaction, a first name and a last name of a consumer and an associated payment method; subsequent to the first transaction, receiving, during a second transaction, with the second merchant device, identity information, the second merchant device being different than the first merchant device; determining that the consumer previously interacted with an affiliate merchant device, the affiliate merchant device being the first merchant device subsequent to the determination that the consumer previously interacted with the affiliate merchant device, matching the identity information received during the second transaction to the first and last name of the consumer received during the first transaction; and identifying, based on the match of the identity information received during the second transaction to the first and last name of the consumer received during the first transaction, a consumer profile associated with the payment method, the consumer profile associated with the email suggestor system; identify, from the consumer profile, an associated email address associated with the consumer profile; providing, during the second transaction, an interface to a third-party payment application; and causing, during the second transaction, display of the email address associated with the consumer profile associated with the payment method configured to reduce the transaction time, subsequent to the identification of the associated email address associated with the consumer profile. 24. The computer-implemented method according to claim 17 , further comprising: in an instance in which the payment information is on file with the first merchant device, generating a form that includes the identity information and the email address; and requesting a response from the consumer.

1. An apparatus for assisting user-selection of achievement tools that meet educational standards, the apparatus comprising: a server computer comprising memory, wherein the memory centrally stores: a plurality of keywords; a plurality of educational standards; a plurality of achievement tools; keyword-to-educational-standard assignments, wherein each of the educational standards has assigned thereto at least selected ones of the keywords; and keyword-to-achievement-tool assignments, wherein each of the achievement tools has assigned thereto at least selected ones of the keywords; wherein the server computer is operable to: publish, over a computer network, a user interface that enables the keyword-to-achievement-tool assignments to be revised, wherein the user interface is configured to enable user log-in via a unique identifier; receive, over the computer network and via the user interface, a keyword-assignment revision with respect to a particular achievement tool of the plurality of achievement tools; and in the memory, revise the at least selected ones of the keywords assigned to the particular achievement tool based, at least in part, on the received keyword-assignment revision.

1. An apparatus for assisting user-selection of achievement tools that meet educational standards, the apparatus comprising: a server computer comprising memory, wherein the memory centrally stores: a plurality of keywords; a plurality of educational standards; a plurality of achievement tools; keyword-to-educational-standard assignments, wherein each of the educational standards has assigned thereto at least selected ones of the keywords; and keyword-to-achievement-tool assignments, wherein each of the achievement tools has assigned thereto at least selected ones of the keywords; wherein the server computer is operable to: publish, over a computer network, a user interface that enables the keyword-to-achievement-tool assignments to be revised, wherein the user interface is configured to enable user log-in via a unique identifier; receive, over the computer network and via the user interface, a keyword-assignment revision with respect to a particular achievement tool of the plurality of achievement tools; and in the memory, revise the at least selected ones of the keywords assigned to the particular achievement tool based, at least in part, on the received keyword-assignment revision. 8. An apparatus as claimed in claim 1 , wherein the server computer is operable to filter the educational standards so that a user is provided only educational standards pertinent to that user.

18. The speech communication system of claim 12 , further comprising: a semantic search unit, the semantic search unit configured to perform a semantic search using taxonomies in order to generate a taxonomy correction factor that is used to calculate the trustworthiness factor.

18. The speech communication system of claim 12 , further comprising: a semantic search unit, the semantic search unit configured to perform a semantic search using taxonomies in order to generate a taxonomy correction factor that is used to calculate the trustworthiness factor. 19. The speech communication system of claim 18 , further comprising: a similarity check unit, the similarity check unit configured to carry out a similarity checking step which takes into account the similarity of various definitions of a respective keyword in order to generate a similarity correction factor that is used to calculate the trustworthiness factor.

11. A non-transitory computer readable medium storing computer program instructions executable by at least one computer processor to perform a method, the method comprising: receiving, from a provider device, a document; extracting at least one item from the received document; determining at least one code based on the at least one extracted item; determining at least one quality measure included in at least one of the at least one code and the at least one extracted item, the at least one quality measure including at least one quality measure criterion; determining if a quality measure criterion of the at least one quality measure criterion remains unsatisfied; and generating a score indicating a performance of quality measures.

11. A non-transitory computer readable medium storing computer program instructions executable by at least one computer processor to perform a method, the method comprising: receiving, from a provider device, a document; extracting at least one item from the received document; determining at least one code based on the at least one extracted item; determining at least one quality measure included in at least one of the at least one code and the at least one extracted item, the at least one quality measure including at least one quality measure criterion; determining if a quality measure criterion of the at least one quality measure criterion remains unsatisfied; and generating a score indicating a performance of quality measures. 12. The computer readable medium of claim 11 , wherein determining at least one code further comprises using a pattern matching and searching algorithm to map identify the at least one code.

18. A method for language identification embodied in at least one computer system, comprising: inputting, by the computer system, a text; dividing, by the computer system, the input text into tokens; detecting, by the computer system, character strings within the tokens from a feature set of a plurality of character strings of varying length with associated information, the associated information including one or more significance scores for a character string for one or more of a plurality of languages, wherein the significance scores include a basic significance score and an additional significance score for at least one of the character strings, wherein the additional significance score is for application in response to detection of a characteristic in a syllable other than the character string within a word containing the character string, and wherein the characteristic comprises the syllable containing a letter matching a letter contained in a predetermined set of one or more letters; and detecting, by the computer system the at least one characteristic in a syllable other than the character string within a word containing the character string within the input text responsive to detecting the character string within the input text.

18. A method for language identification embodied in at least one computer system, comprising: inputting, by the computer system, a text; dividing, by the computer system, the input text into tokens; detecting, by the computer system, character strings within the tokens from a feature set of a plurality of character strings of varying length with associated information, the associated information including one or more significance scores for a character string for one or more of a plurality of languages, wherein the significance scores include a basic significance score and an additional significance score for at least one of the character strings, wherein the additional significance score is for application in response to detection of a characteristic in a syllable other than the character string within a word containing the character string, and wherein the characteristic comprises the syllable containing a letter matching a letter contained in a predetermined set of one or more letters; and detecting, by the computer system the at least one characteristic in a syllable other than the character string within a word containing the character string within the input text responsive to detecting the character string within the input text. 19. The method of claim 18 , further comprising identifying all character strings within the input text and adding the significance scores for a particular language for all character strings identified.

1. A computer-implemented method of analyzing a clinical decision support (CDS) document and improving content analyzer system accuracy, the method comprising: improving content analyzer system accuracy in identifying CDS document deficiencies and consistencies with respect to reference content, the reference content comprising clinical guidelines, by repeatedly training a machine learning module, hosted by a content analyzer system, based on new incoming data, wherein the machine learning module is configured to automatically determine which content features are to be used to determine whether content is to be designated as relevant and matching to the reference content and which content is to be designated as non-relevant and to construct or modify an electronic model accordingly, wherein the features comprise one or more of text length, presence of a medication term, medical intervention language, use of a negation, or context, wherein improving content analyzer system accuracy by training the machine learning module comprises repeatedly: collecting positive and negative cases from CDS documents, training the electronic model using the collected positive and negative cases from CDS documents, taking as input a text segment extracted from a CDS document and returning a likelihood that the text segment matches a reference checklist item, and wherein the new incoming data indicates whether the likelihood that the text segment matches a reference checklist item is correct or incorrect; receiving at a computer system, including hardware and comprising an analytics engine, a clinical decision support document from a medical service provider system; accessing over a network from a remote system, by the computer system, reference content corresponding at least in part to the clinical decision support document, the reference content comprising clinical guidelines; using, by the computer system, the electronic model to identify and extract medical intervention content from the clinical decision support document; using feedback with respect to the identification of the medical intervention content to refine the electronic model; segmenting, by the computer system, at least a portion of the extracted medical intervention content into a first plurality of segments including: at least a first segment, comprising a first set of text, and a second segment comprising a second set of text, wherein a given segment in the first plurality of segments is evaluated to identify a core concept, wherein identifying the core concept further comprises determining whether a given segment includes a plurality of medications, and determining which of the plurality of medications are part of the core concept and which of the plurality of medications are not part of the core concept, and if the core concept of the given segment comprises at least one a medical intervention, determining whether a negation is associated with the at least one medical intervention; determining, by the trained machine learning engine, if the first segment corresponds to at least a first item included in the reference content, the first item comprising a third set of text comprising terminology not present in the first and second sets of text; at least partly in response to determining that the first segment, comprising the first set of text, corresponds to the first item included in the reference content, the first item comprising the third set of text, causing a version of the clinical decision support document to be generated to include a visual indication that the first segment corresponds to the first item included in the reference content; determining, by the trained machine learning engine, if a second item included in the reference content corresponds to at least one of the first plurality of segments; at least partly in response to determining that the second item included in the reference content does not correspond to at least one of the first plurality of segments, causing the version of the clinical decision support document to be generated to include a visual indication that the first plurality of segments fails to include at least one segment that corresponds to the second item included in the reference content; and at least partly in response to determining that the second item included in the reference content does correspond to at least one of the first plurality of segments, causing the version of the clinical decision support document to include a visual indication that the second item corresponds to at least one segment in the first plurality of segments.

1. A computer-implemented method of analyzing a clinical decision support (CDS) document and improving content analyzer system accuracy, the method comprising: improving content analyzer system accuracy in identifying CDS document deficiencies and consistencies with respect to reference content, the reference content comprising clinical guidelines, by repeatedly training a machine learning module, hosted by a content analyzer system, based on new incoming data, wherein the machine learning module is configured to automatically determine which content features are to be used to determine whether content is to be designated as relevant and matching to the reference content and which content is to be designated as non-relevant and to construct or modify an electronic model accordingly, wherein the features comprise one or more of text length, presence of a medication term, medical intervention language, use of a negation, or context, wherein improving content analyzer system accuracy by training the machine learning module comprises repeatedly: collecting positive and negative cases from CDS documents, training the electronic model using the collected positive and negative cases from CDS documents, taking as input a text segment extracted from a CDS document and returning a likelihood that the text segment matches a reference checklist item, and wherein the new incoming data indicates whether the likelihood that the text segment matches a reference checklist item is correct or incorrect; receiving at a computer system, including hardware and comprising an analytics engine, a clinical decision support document from a medical service provider system; accessing over a network from a remote system, by the computer system, reference content corresponding at least in part to the clinical decision support document, the reference content comprising clinical guidelines; using, by the computer system, the electronic model to identify and extract medical intervention content from the clinical decision support document; using feedback with respect to the identification of the medical intervention content to refine the electronic model; segmenting, by the computer system, at least a portion of the extracted medical intervention content into a first plurality of segments including: at least a first segment, comprising a first set of text, and a second segment comprising a second set of text, wherein a given segment in the first plurality of segments is evaluated to identify a core concept, wherein identifying the core concept further comprises determining whether a given segment includes a plurality of medications, and determining which of the plurality of medications are part of the core concept and which of the plurality of medications are not part of the core concept, and if the core concept of the given segment comprises at least one a medical intervention, determining whether a negation is associated with the at least one medical intervention; determining, by the trained machine learning engine, if the first segment corresponds to at least a first item included in the reference content, the first item comprising a third set of text comprising terminology not present in the first and second sets of text; at least partly in response to determining that the first segment, comprising the first set of text, corresponds to the first item included in the reference content, the first item comprising the third set of text, causing a version of the clinical decision support document to be generated to include a visual indication that the first segment corresponds to the first item included in the reference content; determining, by the trained machine learning engine, if a second item included in the reference content corresponds to at least one of the first plurality of segments; at least partly in response to determining that the second item included in the reference content does not correspond to at least one of the first plurality of segments, causing the version of the clinical decision support document to be generated to include a visual indication that the first plurality of segments fails to include at least one segment that corresponds to the second item included in the reference content; and at least partly in response to determining that the second item included in the reference content does correspond to at least one of the first plurality of segments, causing the version of the clinical decision support document to include a visual indication that the second item corresponds to at least one segment in the first plurality of segments. 9. The method as defined in claim 1 , the method further comprising: determining whether a first character string in the clinical decision support document exceeds a first number of words or characters; and at least partly in response to determining that the first character string in the clinical decision support document exceeds the first number of words or characters, excluding the first character string from the first plurality of segments.

1. A system for knowledge representation in a computer that can enable natural language communication with a computer, the system comprising: at least one hardware processor; at least one database configured to store at least one table, the at least one table configured to store associations between concepts in a body of text and associated concept identifiers; and a builder interfaced with the database, the builder configured to, when executed by the at least one hardware processor, construct a table that represents knowledge defined by a body of text comprising words and punctuation, the construction of the table comprising assigning a unique identifier to an observation concept defined by the body of text, building a tree comprising a plurality of sub-concepts by breaking the observation concept into sub-concepts by identifying a subject concept, a seam concept, and a relative concept, and joining sub-concepts into higher order sub-concepts until two or more sub-concepts join to form the concept, wherein said joining comprises constructing a binary concept by either joining the subject concept and the seam concept or joining the seam concept and the relative concept, and constructing a first higher order sub-concept by joining either the relative concept or the subject concept with the binary concept, assigning unique identifiers to each of the plurality of sub-concepts including the subject concept, the seam concept, the relative concept, the binary concept, and the first higher order sub-concept, wherein the unique identifiers assigned to the observation concept and each of the plurality of sub-concepts are generated according to the same scheme, and storing each of the concept and plurality of sub-concepts in a row in the at least one table, wherein each row comprises the concept or sub-concept, the unique identifier assigned to the concept or sub-concept, and the unique identifiers assigned to two or more lower order sub-concepts, if any, which were joined to form the concept or sub-concept; wherein the plurality of sub-concepts comprise at least each of the words and punctuation in the body of text.

1. A system for knowledge representation in a computer that can enable natural language communication with a computer, the system comprising: at least one hardware processor; at least one database configured to store at least one table, the at least one table configured to store associations between concepts in a body of text and associated concept identifiers; and a builder interfaced with the database, the builder configured to, when executed by the at least one hardware processor, construct a table that represents knowledge defined by a body of text comprising words and punctuation, the construction of the table comprising assigning a unique identifier to an observation concept defined by the body of text, building a tree comprising a plurality of sub-concepts by breaking the observation concept into sub-concepts by identifying a subject concept, a seam concept, and a relative concept, and joining sub-concepts into higher order sub-concepts until two or more sub-concepts join to form the concept, wherein said joining comprises constructing a binary concept by either joining the subject concept and the seam concept or joining the seam concept and the relative concept, and constructing a first higher order sub-concept by joining either the relative concept or the subject concept with the binary concept, assigning unique identifiers to each of the plurality of sub-concepts including the subject concept, the seam concept, the relative concept, the binary concept, and the first higher order sub-concept, wherein the unique identifiers assigned to the observation concept and each of the plurality of sub-concepts are generated according to the same scheme, and storing each of the concept and plurality of sub-concepts in a row in the at least one table, wherein each row comprises the concept or sub-concept, the unique identifier assigned to the concept or sub-concept, and the unique identifiers assigned to two or more lower order sub-concepts, if any, which were joined to form the concept or sub-concept; wherein the plurality of sub-concepts comprise at least each of the words and punctuation in the body of text. 3. The system of claim 1 , wherein the construction of the table further comprises constructing a post-modifier concept and assigning a unique identifier to the post-modifier concept, and forming a second higher order sub-concept by joining the post-modifier concept with the first higher order sub-concept and assigning a unique identifier to the second higher order sub-concept.

20. In a data processing system for composing documents having multiple lines of alphanumeric data comprising: means for entering data and commands relating to a document to be composed; data processor means for processing said data and for executing commands; memory means for storing data and commands; a plurality of data presentation output means for presenting the document in a final form; means for selecting a first format for defining data presentation characteristics for at least a first portion of the document and for associating a first abstract format name with the first format upon entry of said first abstract format name via said means for entering; means for defining a first set of data presentation characteristics for a first data presentation output means and for associating said first set of characteristics with said first abstract format name; means for defining a second set of data presentation characteristics, which are independent from said first set of data presentation characteristics, for a second data presentation output means without affecting the data presentation characteristics defined for said first data presentation output means and for associating said second set of data presentation characteristics with said first abstract format name; means for associating with every line in the document an abstract format name which is linked to a data presentation characteristic defining format; means responsive to the entry of said first abstract format name for formatting the lines in the document on said first data presentation means to correspond with said first set of data presentation characteristics and for formatting the lines on said second data presentation output means to correspond with said second set of data presentation characteristics; and means for displaying the document during composition in a form substantially the same as the final form display.

20. In a data processing system for composing documents having multiple lines of alphanumeric data comprising: means for entering data and commands relating to a document to be composed; data processor means for processing said data and for executing commands; memory means for storing data and commands; a plurality of data presentation output means for presenting the document in a final form; means for selecting a first format for defining data presentation characteristics for at least a first portion of the document and for associating a first abstract format name with the first format upon entry of said first abstract format name via said means for entering; means for defining a first set of data presentation characteristics for a first data presentation output means and for associating said first set of characteristics with said first abstract format name; means for defining a second set of data presentation characteristics, which are independent from said first set of data presentation characteristics, for a second data presentation output means without affecting the data presentation characteristics defined for said first data presentation output means and for associating said second set of data presentation characteristics with said first abstract format name; means for associating with every line in the document an abstract format name which is linked to a data presentation characteristic defining format; means responsive to the entry of said first abstract format name for formatting the lines in the document on said first data presentation means to correspond with said first set of data presentation characteristics and for formatting the lines on said second data presentation output means to correspond with said second set of data presentation characteristics; and means for displaying the document during composition in a form substantially the same as the final form display. 32. Apparatus according to claim 20, wherein the first abstract format name includes at least one field, further including means for associating a set of data presentation characteristics with each field in the named format; means for associating a set of data presentation characteristics for each of a plurality of output means; and means for controlling the presentation of data on each of said output means based upon the data presentation characteristics defined by the first abstract named format and its associated data presentation characteristics.

28. The method of claim 25 , further comprising: determining said preferred language associated with said request.

28. The method of claim 25 , further comprising: determining said preferred language associated with said request. 29. The method of claim 28 , wherein: determining said preferred language includes determining said preferred language from at least one of a Uniform Resource Locator (URL) associated with said request, a hypertext transfer protocol (HTTP) header variable associated with said request, an identity profile associated with said request, and a cookie associated with said request.

1. An apparatus for transferring storage devices within an automated storage library, comprising: a frame; a translation member for translating relative to the frame, wherein the translation member includes a leadnut operable to translate along a leadscrew; a finger mechanism slidably mounted to the frame, the finger mechanism having a finger member for engaging a storage device, wherein the finger mechanism is mechanically associated with the translation member, and movement of the translation member results in relative movement of the finger mechanism to the translation member such that the finger mechanism moves a distance different than that of the translation member; and a gear assembly rotatably mounted to the leadnut, wherein a first portion of the gear assembly engages a portion of the frame and a second portion of the gear assembly engages a portion of the finger mechanism such that translation of the leadnut results in relative movement of the finger mechanism to the leadnut.

1. An apparatus for transferring storage devices within an automated storage library, comprising: a frame; a translation member for translating relative to the frame, wherein the translation member includes a leadnut operable to translate along a leadscrew; a finger mechanism slidably mounted to the frame, the finger mechanism having a finger member for engaging a storage device, wherein the finger mechanism is mechanically associated with the translation member, and movement of the translation member results in relative movement of the finger mechanism to the translation member such that the finger mechanism moves a distance different than that of the translation member; and a gear assembly rotatably mounted to the leadnut, wherein a first portion of the gear assembly engages a portion of the frame and a second portion of the gear assembly engages a portion of the finger mechanism such that translation of the leadnut results in relative movement of the finger mechanism to the leadnut. 6. The apparatus of claim 1 , wherein the finger assembly is adapted to engage a storage device.

15. The non-transitory computer readable storage medium of claim 11 further comprising the step of transmitting search suggestions related to content during the populating of the search interface with the content.

15. The non-transitory computer readable storage medium of claim 11 further comprising the step of transmitting search suggestions related to content during the populating of the search interface with the content. 16. The non-transitory computer readable storage medium of claim 15 wherein the software code configured to detect the user-initiated search execution trigger further comprises the software code being configured to detect selection of a search suggestion in the displayed search suggestions.

1. A method of analyzing a turbine engine to determine a normal engine condition or a faulty engine condition, said method comprising the steps of: acquiring at least one engine operating parameter; calculating at least one engine residual value from said at least one engine operating parameter; normalizing said at least one engine residual value to yield at least one normalized engine residual; mapping, via a clustering technique, said at least one normalized engine residual as at least one input vector into an engine condition space having a plurality of clusters, each of said plurality of clusters representing either a normal vector engine condition or a faulty vector engine condition; identifying a closest cluster within said engine condition space, said closest cluster being closer to said at least one input vector than any other of said plurality of clusters; and determining a normal engine condition for the engine undergoing analysis if said closest cluster represents a normal vector engine condition, and determining a faulty engine condition for the engine undergoing analysis if said closest cluster represents a faulty vector engine condition.

1. A method of analyzing a turbine engine to determine a normal engine condition or a faulty engine condition, said method comprising the steps of: acquiring at least one engine operating parameter; calculating at least one engine residual value from said at least one engine operating parameter; normalizing said at least one engine residual value to yield at least one normalized engine residual; mapping, via a clustering technique, said at least one normalized engine residual as at least one input vector into an engine condition space having a plurality of clusters, each of said plurality of clusters representing either a normal vector engine condition or a faulty vector engine condition; identifying a closest cluster within said engine condition space, said closest cluster being closer to said at least one input vector than any other of said plurality of clusters; and determining a normal engine condition for the engine undergoing analysis if said closest cluster represents a normal vector engine condition, and determining a faulty engine condition for the engine undergoing analysis if said closest cluster represents a faulty vector engine condition. 10. The method of claim 1 wherein said step of normalizing comprises the step of normalizing a standard derivation of said at least one engine residual value to unity.

1. An alarm system controller comprising: (a) a packet data network interface port; (b) a security alarm system interface port configured to communicate with security alarm sensors; and (c) a controller configured to receive at least one input from the security alarm system interface port, to process the at least one input to determine an alarm condition, and to communicate the alarm condition within information defining a markup language interface through the packet data network interface port.

1. An alarm system controller comprising: (a) a packet data network interface port; (b) a security alarm system interface port configured to communicate with security alarm sensors; and (c) a controller configured to receive at least one input from the security alarm system interface port, to process the at least one input to determine an alarm condition, and to communicate the alarm condition within information defining a markup language interface through the packet data network interface port. 8. The alarm system controller according to claim 1 , wherein the controller is further configured to communicate with a browser human user interface using the information defining the markup language interface.

1. A method of classifying the material type of an unknown material into a probability distribution of multiple predetermined material types by using a collection of plural predetermined material classifiers, wherein each material type of the multiple predetermined material types is associated with a corresponding best performing classifier from the collection of plural predetermined material classifiers by a predesignated stored association, the method comprising the steps of: applying, using a processor, the plural material classifiers to the unknown material to obtain a list of candidate material types; looking up, using the processor, a list of potential best performing classifiers using the list of candidate material types as a reference into the predesignated stored association; and assigning, using the processor, a respective probability that the unknown material belongs to a material type based on the list of potential best performing classifiers, wherein applying comprises obtaining one or more feature vectors for the unknown material and inputting a corresponding one of the feature vectors into each of the plural material classifiers so as to obtain an output representative of material type from each of the plural material classifiers.

1. A method of classifying the material type of an unknown material into a probability distribution of multiple predetermined material types by using a collection of plural predetermined material classifiers, wherein each material type of the multiple predetermined material types is associated with a corresponding best performing classifier from the collection of plural predetermined material classifiers by a predesignated stored association, the method comprising the steps of: applying, using a processor, the plural material classifiers to the unknown material to obtain a list of candidate material types; looking up, using the processor, a list of potential best performing classifiers using the list of candidate material types as a reference into the predesignated stored association; and assigning, using the processor, a respective probability that the unknown material belongs to a material type based on the list of potential best performing classifiers, wherein applying comprises obtaining one or more feature vectors for the unknown material and inputting a corresponding one of the feature vectors into each of the plural material classifiers so as to obtain an output representative of material type from each of the plural material classifiers. 13. The method according to claim 1 , wherein the predesignated stored association by which each material type is associated with a corresponding best performing classifier is based on theoretical behavior of the classifiers on the material types.

1. A method of creating a physically based crank-resolved simplified computer implementable engine model, the method comprising: obtaining a complete crank-resolved computer implementable engine model, wherein the complete crank-resolved computer implementable engine model is operable to simulate engine operation of the entire engine, including simulating wave-action effects throughout the engine, and produce outputs based on parametric inputs to the engine; selecting, from the complete crank-resolved computer implementable engine model, one or more elements defining start and end points of the physically based crank-resolved simplified computer implementable engine model which is to be created; obtaining from a library of rules, at least one computer implementable model creation rule corresponding to the one or more selected elements; creating, using a computer, the physically based crank-resolved simplified computer implementable engine model using the at least one computer implementable model creation rule, wherein the physically based crank-resolved simplified computer implementable engine model is also operable to simulate engine operation, including simulating wave-action effects throughout the simplified engine model, and produce outputs in real time based on the parametric inputs to the engine; wherein said simplified computer implementable engine model employs an approximation for a mathematical function employed by the complete crank-resolved engine model, comprising: identifying an operation which the complete crank-resolved engine model employs, for which a corresponding mathematical function requires a complex numerical algorithm; obtaining an approximation to the mathematical function which requires a simplified algorithm; and generating a control rule under which, when a simplified engine model implementing the operation is created from the complete crank-resolved engine model, the approximation will be employed instead of the mathematical function, and wherein said generated control rule is stored in a module which is operable to create a simplified engine model from the complete crank-resolved engine model; and simulating engine operation, including simulating wave-action effects throughout the simplified engine model, using the computer and the physically based crank-resolved simplified computer implementable engine model.

1. A method of creating a physically based crank-resolved simplified computer implementable engine model, the method comprising: obtaining a complete crank-resolved computer implementable engine model, wherein the complete crank-resolved computer implementable engine model is operable to simulate engine operation of the entire engine, including simulating wave-action effects throughout the engine, and produce outputs based on parametric inputs to the engine; selecting, from the complete crank-resolved computer implementable engine model, one or more elements defining start and end points of the physically based crank-resolved simplified computer implementable engine model which is to be created; obtaining from a library of rules, at least one computer implementable model creation rule corresponding to the one or more selected elements; creating, using a computer, the physically based crank-resolved simplified computer implementable engine model using the at least one computer implementable model creation rule, wherein the physically based crank-resolved simplified computer implementable engine model is also operable to simulate engine operation, including simulating wave-action effects throughout the simplified engine model, and produce outputs in real time based on the parametric inputs to the engine; wherein said simplified computer implementable engine model employs an approximation for a mathematical function employed by the complete crank-resolved engine model, comprising: identifying an operation which the complete crank-resolved engine model employs, for which a corresponding mathematical function requires a complex numerical algorithm; obtaining an approximation to the mathematical function which requires a simplified algorithm; and generating a control rule under which, when a simplified engine model implementing the operation is created from the complete crank-resolved engine model, the approximation will be employed instead of the mathematical function, and wherein said generated control rule is stored in a module which is operable to create a simplified engine model from the complete crank-resolved engine model; and simulating engine operation, including simulating wave-action effects throughout the simplified engine model, using the computer and the physically based crank-resolved simplified computer implementable engine model. 3. The method as claimed in claim 1 wherein the elements defining the simplified model comprise a start point and/or end point from within the complete crank-resolved engine model.

11. A method comprising: causing display of at least a portion of an interface that includes an input field configured to enable a user to enter input to define a search query; receiving first search input entered in the input field included in the interface; after receiving the first search input entered in the input field included in the interface: accessing a first search query based on the first search input entered in the input field included in the interface; initiating performance of a first search to identify search results that are responsive to the first search query; based on the first search to identify search results that are responsive to the first search query, accessing a first list of search results that are responsive to the first search query, the first list of search results including at least a first search result that is responsive to the first search query and that links to first electronic content; and causing display of the first list of search results accessed based on the first search to identify search results that are responsive to the first search query, the display of the first list of search results having a representation of the first search result that includes description information that is descriptive of the first search result and a first link that links to the first electronic content; after causing display of the first list of search results accessed based on the first search to identify search results that are responsive to the first search query, detecting user input selecting the first search result included in the display of the first list of search results; in response to the detection of user input selecting the first search result included in the display of the first list of search results, automatically, by at least one processor and without additional user input after the user input selecting the first search result, including the first search result in a second list of search results that is different from the first list of search results, that, when displayed, includes a reformatted representation of the first search result that has reduced description information of the first search result as compared to the description information included in the representation of the first search result in the display of the first list of search results, and that, when displayed, includes at least one interface control that enables a user to add, to the first search result included in the second list of search results, a comment that is displayed in the second list of search results in association with the reformatted representation of the first search result; and after accessing search results based on a second search to identify search results that are responsive to a second search query that is different than the first search query and that was accessed after automatically including the first search result in the second list of search results, including, in the second list of search results, a second search result identified in the second search such that the second list of search results includes the first search result which is responsive to the first search query and the second search result which is responsive to the second search query.

11. A method comprising: causing display of at least a portion of an interface that includes an input field configured to enable a user to enter input to define a search query; receiving first search input entered in the input field included in the interface; after receiving the first search input entered in the input field included in the interface: accessing a first search query based on the first search input entered in the input field included in the interface; initiating performance of a first search to identify search results that are responsive to the first search query; based on the first search to identify search results that are responsive to the first search query, accessing a first list of search results that are responsive to the first search query, the first list of search results including at least a first search result that is responsive to the first search query and that links to first electronic content; and causing display of the first list of search results accessed based on the first search to identify search results that are responsive to the first search query, the display of the first list of search results having a representation of the first search result that includes description information that is descriptive of the first search result and a first link that links to the first electronic content; after causing display of the first list of search results accessed based on the first search to identify search results that are responsive to the first search query, detecting user input selecting the first search result included in the display of the first list of search results; in response to the detection of user input selecting the first search result included in the display of the first list of search results, automatically, by at least one processor and without additional user input after the user input selecting the first search result, including the first search result in a second list of search results that is different from the first list of search results, that, when displayed, includes a reformatted representation of the first search result that has reduced description information of the first search result as compared to the description information included in the representation of the first search result in the display of the first list of search results, and that, when displayed, includes at least one interface control that enables a user to add, to the first search result included in the second list of search results, a comment that is displayed in the second list of search results in association with the reformatted representation of the first search result; and after accessing search results based on a second search to identify search results that are responsive to a second search query that is different than the first search query and that was accessed after automatically including the first search result in the second list of search results, including, in the second list of search results, a second search result identified in the second search such that the second list of search results includes the first search result which is responsive to the first search query and the second search result which is responsive to the second search query. 13. The method of claim 11 , wherein including, in the second list of search results, a second search result identified in the second search comprises including the second search result at an end of the second list of search results immediately following the first search result.

20. The method of claim 13 , wherein the set of patent features includes IPC-overlap, representing the number of the overlapping IPC codes between the IPC codes of a patent in the first set of candidate patent documents and the IPC codes of an initial high-ranking set of patent documents in the first set of candidate patent documents, the re-ranking module further adapted to compute IPC-overlap including code adapted to define the overlap score between two IPC codes, divide each IPC code to a plurality of levels based on IPC code structure, and wherein a first level overlap between two IPC codes results in a first score and a second level overlap between two IPC codes results in a second score.

20. The method of claim 13 , wherein the set of patent features includes IPC-overlap, representing the number of the overlapping IPC codes between the IPC codes of a patent in the first set of candidate patent documents and the IPC codes of an initial high-ranking set of patent documents in the first set of candidate patent documents, the re-ranking module further adapted to compute IPC-overlap including code adapted to define the overlap score between two IPC codes, divide each IPC code to a plurality of levels based on IPC code structure, and wherein a first level overlap between two IPC codes results in a first score and a second level overlap between two IPC codes results in a second score. 21. The method of claim 20 , wherein the IPC-overlap of a given patent document is an average overlap scores between the IPC codes of that patent document and all the IPC codes of the initial high-ranking set of patent documents.

25. The computer program product of claim 19 further comprising means, recorded on the recording medium, for creating a presentation document, including: means, recorded on the recording medium, for creating, in dependence upon an original document, a structured document comprising one or more structural elements; means, recorded on the recording medium, for classifying a structural element of the structured document according to a presentation attribute; and means, recorded on the recording medium, for creating a presentation grammar for the structured document, wherein the presentation grammar for the structured document includes grammar elements each of which includes an identifier for at least one structural element of the structured document.

25. The computer program product of claim 19 further comprising means, recorded on the recording medium, for creating a presentation document, including: means, recorded on the recording medium, for creating, in dependence upon an original document, a structured document comprising one or more structural elements; means, recorded on the recording medium, for classifying a structural element of the structured document according to a presentation attribute; and means, recorded on the recording medium, for creating a presentation grammar for the structured document, wherein the presentation grammar for the structured document includes grammar elements each of which includes an identifier for at least one structural element of the structured document. 27. The computer program product of claim 25 wherein means, recorded on the recording medium, for creating a presentation grammar for the structured document comprises: means, recorded on the recording medium, for identifying the content type of the original document; means, recorded on the recording medium, for selecting, in dependence upon the content type, a full presentation grammar from among a multiplicity of full presentation grammars; and means, recorded on the recording medium, for filtering the full presentation grammar into a presentation grammar for the structured document in dependence upon the structural elements of the structured document.

21. The system according to claim 14 , wherein said user interface provides options for structuring cluster analysis.

21. The system according to claim 14 , wherein said user interface provides options for structuring cluster analysis. 22. The system according to claim 21 , wherein said options for structuring cluster analysis include at least one member selected from the group comprising types of cluster analysis and parameters stipulating the number of analyses to be conducted.

12. A spinal fixation system, comprising: a bone anchor having a bone-engaging portion and a spinal fixation element receiving portion with opposed arms configured to receive a spinal fixation element therebetween; a connecting member having first and second ends with a spanning portion extending therebetween; a connecting assembly having a distal surface that bears against a proximal terminal end surface of each of the opposed arms of the rod receiving portion of the bone anchor and a receiving portion that is configured to receive a portion of the connecting member.

12. A spinal fixation system, comprising: a bone anchor having a bone-engaging portion and a spinal fixation element receiving portion with opposed arms configured to receive a spinal fixation element therebetween; a connecting member having first and second ends with a spanning portion extending therebetween; a connecting assembly having a distal surface that bears against a proximal terminal end surface of each of the opposed arms of the rod receiving portion of the bone anchor and a receiving portion that is configured to receive a portion of the connecting member. 18. The system of claim 12 , further comprising: a second bone anchor having a bone-engaging portion and a spinal fixation receiving portion with opposed arms configured to receive a spinal fixation element therebetween; and a second connecting assembly having a distal surface that bears against a proximal terminal end surface of each of the opposed arms of the rod receiving portion of the bone anchor and a receiving portion that is configured to receive a portion of the connecting member.