Patent Publication Number: US-7904411-B2

Title: Knowledge discovery tool relationship generation

Description:
RELATED APPLICATIONS 
     The present patent document is a continuation-in-part of application Ser. No. 11/051,745 filed Feb. 4, 2005 now abandoned, the entire disclosure of which is hereby incorporated by reference. 
    
    
     COPYRIGHT NOTICE 
     A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever. The following notice applies to any software and data as described below and in the drawings hereto: Copyright©  2004 , Accenture, All Rights Reserved. 
     BACKGROUND 
     1. Technical Field 
     The present invention relates generally to an improved method for obtaining, managing, and providing complex, detailed information stored in electronic form in a plurality of sources. The invention may find particular use in organizations that have a need to discover relationships among various pieces of information in a given field. 
     2. Background Information 
     With the advent of the Internet, the Information Age is upon us. Today, one can find vast amounts of information about any given field or topic at the touch of a button. This information may be available from myriad sources in a variety of commonly recognized formats, such as XML, flat-files, HTML, text, spreadsheets, presentations, diagrams, programming code, databases, etc. This information may also be kept in third-party proprietary formats. 
     Amid this apparent wealth of online information, people still have problems finding the information they need. Online information retrieval may have problems including those related to inappropriate user interface designs and to poor or inappropriate organization and structure of the information. Additionally, the storage of information online in the variety of formats described above also leads to retrieval problems. 
     The existence of a variety of information sources leads to many problems. First, there is a lack of a unified information space. An “information space” is the set of all sources of information that is available to a user at a given time or setting. When information is stored in many formats and at many sources, a user is forced to spend too much overhead on discovering and remembering where different information is located (e.g., web pages, online databases, etc). The user also spends a large amount of time remembering how to find information in each delivery mechanism. Thus, it is difficult for the user to remember where potentially relevant information might be, and the user is forced to jump between multiple different tools to find it. 
     The existence of a variety of information sources also leads to information discovery strategies that lack cohesion. Users must learn to use and remember a variety of metaphors, user interfaces, and searching techniques for each delivery mechanism and class of information. Other problems associated with large numbers of information sources include a lack of links between information sources, and poor delivery mechanisms that don&#39;t provide a global view of the information space. 
     To overcome these problems, knowledge discovery tools have been developed. These tools extract information from a plurality of data sources, integrate the information into a common data model, and provide a graphical user interface for viewing the information. While these types of systems have been useful for unifying the information space for a given domain, they still suffer from several limitations. 
     First, each of these data sources typically includes a large volume of files. Thus, collecting and integrating information from a particular data source consumes both time and resources. However, in order to truly represent the information space for a given domain, these tools must collect data from many data sources. Each data source added to the process becomes an additional strain on both resources and time. Moreover, this information must be processed repeatedly to ensure that the data model includes the most current information. Present systems will process a data source in its entirety each and every time an extraction and integration cycle take place. Accordingly, there is a need for a system that doesn&#39;t waste time and resources re-integrating information that has already been integrated into the data model. 
     Second, integrating information from a plurality of data sources also leads to problems in the consistency of the information contained in the data model. Information in the data model may be overwritten by less reliable data. For example, a particular person&#39;s name may be found in both a structured database maintained by the IRS and the text of an email. In present systems, the name sourced from the email may be used to overwrite the name obtained from the IRS if the email is integrated later. Because the information maintained by the IRS is inherently more reliable than the text of an email (because of both source credibility and structured data), there is a need for a system that takes into account the reliability of the information maintained by the data sources before integrating that information into the data model. 
     Third, the information integrated into the data model is inherently related as that information defines the information space for a given domain. Unfortunately, present systems do not fully realize these interrelationships. Typically, relationships between the data in the knowledge must be defined manually. Manually defining these relationships, however, is a time consuming and expensive process. While systems automatically incorporate those relationships maintained by a particular data source (for example, relationships defined by a database data source), these relationships only represent a fraction of the relationships present among the information contained in the data model. Accordingly, there is a need for a system automatically discovering and generating various types of relationships. 
     The present invention provides a robust technique for integrating, from a plurality of data sources, only the necessary, most reliable data into a data model, and automatically discovering inter-relationships among the various elements of the data model. 
     BRIEF SUMMARY 
     In one embodiment, a system for managing a knowledge model defining a plurality of entities is provided. The system includes an extraction tool for extracting data items from disparate data sources that determines if the data item has been previously integrated into the knowledge model. The system also includes an integration tool for integrating the data item into the knowledge model that integrates the data item into the knowledge model only if the data item has not been previously integrated into the knowledge model. Additionally, a relationship tool for identifying, automatically, a plurality of relationships between the plurality of entities may also be provided. The system may also include a data visualization tool for presenting the plurality of entities and the plurality of relationships. 
     In another embodiment, a method for determining a relationship between a plurality of entities of a knowledge model is provided, where the knowledge model having a plurality of entity tables, each of the plurality of entity tables including a plurality of records, each of the plurality of records having a plurality of fields. The method may include retrieving a first relationship definition, the first relationship definition defining a relationship between a first field and a second field, retrieving a second relationship definition, the second defining a relationship between a third field and a fourth field, and generating, automatically, a transitive relationship definition based in part on the first relationship definition and the second relationship definition. 
     These and other embodiments and aspects of the invention are described with reference to the noted Figures and the below detailed description of the preferred embodiments. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a diagram representative of an embodiment of a knowledge discovery tool in accordance with an embodiment of the present invention; 
         FIG. 2A  is a diagram representative of tables of an exemplary knowledge model in accordance with an embodiment of the present invention; 
         FIG. 2B  is a diagram representative of a field-to-field relationship in accordance with an embodiment of the present invention; 
         FIG. 2C  a diagram representative of a field-to-text relationship in accordance with an embodiment of the present invention; 
         FIG. 3  is a diagram representative of an exemplary workflow for an extraction tool in accordance with an embodiment of the present invention; 
         FIG. 4  is a diagram representative of an exemplary workflow for a compare tool in accordance with an embodiment of the present invention; 
         FIG. 5  is a diagram representative of an exemplary workflow for an integration tool in accordance with an embodiment of the present invention; 
         FIG. 6  is a diagram representative of an exemplary workflow for an integrate tool in accordance with an embodiment of the present invention; 
         FIG. 7  is a diagram representative of an exemplary workflow for loading the information of a received message in accordance with an embodiment of the present invention; 
         FIG. 8  is a diagram representative of an exemplary workflow for a Thesaurus component in accordance with an embodiment of the present invention; 
         FIG. 9  is a diagram representative of an exemplary workflow for a Merge component in accordance with an embodiment of the present invention; 
         FIG. 10  is a diagram representative of an exemplary workflow for a LookUp component in accordance with an embodiment of the present invention; 
         FIG. 11  is a diagram representative of an exemplary workflow for a Compare component in accordance with an embodiment of the present invention; 
         FIG. 12  is a diagram representative of an exemplary workflow for an Insert component in accordance with an embodiment of the present invention; 
         FIG. 13  is a diagram representative of an exemplary workflow for a Update component in accordance with an embodiment of the present invention; 
         FIG. 14  is a diagram representative of an exemplary relationship generation tool in accordance with an embodiment of the present invention; 
         FIG. 15  is an exemplary screen shot of a navigator tool in accordance with an embodiment of the present invention; 
         FIG. 16  is a diagram of exemplary components of a navigator tool in accordance with an embodiment of the present invention; 
         FIG. 17  is an exemplary layout for a navigation tool in accordance with an embodiment of the present invention; 
         FIGS. 18A-E  are exemplary screen shots of a navigator tool in accordance with an embodiment of the present invention; 
         FIG. 19  is an exemplary screen shot of a navigation toolbar in accordance with an embodiment of the present invention; 
         FIG. 20  is an exemplary screen shot of a history dialogue window in accordance with an embodiment of the present invention; 
         FIG. 21  is an exemplary screen shot of a master options dialog in accordance with an embodiment of the present invention; 
         FIG. 22  is an exemplary screen shot of a search tool in accordance with an embodiment of the present invention; 
         FIG. 23A-B  are exemplary screen shots of a navigator with a bookmark list in accordance with an embodiment of the present invention; 
         FIGS. 24A-L  are exemplary screen shots of a wizard service in accordance with an embodiment of the present invention; 
         FIG. 25  is an exemplary screen shot of a monitored items dialog in accordance with an embodiment of the present invention; and 
         FIGS. 26A-E  are exemplary screen shots of a filters dialog in accordance with an embodiment of the present invention. 
     
    
    
     DETAILED DESCRIPTION OF THE DRAWINGS AND THE PRESENTLY PREFERRED EMBODIMENTS 
     Referring now to the drawings, and particularly to  FIG. 1 , there is shown an embodiment of a knowledge discovery system  100  in accordance with the present invention. While the preferred embodiments disclosed herein contemplate a knowledge model based on an information space for pharmaceutical research and the information and data sources related thereto, the present invention is equally applicable for knowledge discovery for any information space defined in any type of data source. Examples of information spaces include software development, drug development, financial research, governmental data administration, and clinical trials, product development and testing etc. 
     The knowledge discovery system in the embodiment of  FIG. 1  includes an extraction tool  120 , an integration tool  130 , a knowledge model  140 , a user information database  145 , a middle tier  150 , and a web server  160 . The extraction tool  120  extracts relevant information from a plurality of data sources  110   a ,  110   b , and  110   x . Optionally, the extraction tool  120  may convert the information into a common format  125 , such as XML. Preferably, the extraction tool  120  is implemented using BIZTALK SERVER, provided by Microsoft Corporation of Redmond, Wash. Once relevant information is extracted, the integration tool  130  incorporates the information into the knowledge model  140 . Preferably, the integration tool is implemented as a COM+application, using the COMPONENT OBJECT MODEL software architecture provided by Microsoft Corporation of Redmond Wash. Finally, the middle tier  150  and optional web server  160  are provided to present the information contained in the knowledge model  140  via a navigator tool  170 . Preferably, the middle tier is implemented using the .NET framework for Web services and component software provided by Microsoft Corporation of Redmond, Wash. Optionally, access to the knowledge model  140  via the navigator  170  may be restricted to registered users. User information may be stored in the user information database  145 . 
     Referring now to  FIGS. 2A-C , an exemplary knowledge model  140  for use in one embodiment of the knowledge discovery system  100  is shown. In the embodiment of  FIGS. 2A-C , the knowledge model  140  defines an information space  200  for pharmaceutical research, and is represented by a relational database consisting of four distinct types of types. Entity tables define the content of the information space  200 . In one embodiment, each entity table may include a name field (which may or may not be the primary key for that table) and attribute fields. Exemplary entity tables are shown in  FIG. 2A . 
     Next, the compare tool  330  of the extraction tool  120  compares the records or documents  315   a ,  315   b  with those records or documents  315   a ,  315   b  that have already been integrated into the knowledge model so that only records or documents  315   a ,  315   b  that are new are further processed. As used herein, a new record or document  315   a ,  315   b  includes records or documents  315   a ,  315   b  that have been integrated into the knowledge model  140 , but have since been modified. In other words, previously entered records or documents  315   a  and  315   b  may include only those records or documents that have been integrated into the knowledge model  140  and have not changed since their integration. In one embodiment, compare tool  330  will compute a value based on the record or document  315   a ,  315   b  . Preferably, the compare tool  330  uses a hash function to generate a hash value for each record or document  315   a ,  315   b  . The value may be based on any part of the record or document  315   a ,  315   b  , such as the identifier or the information contained therein. 
     Referring now to  FIG. 4 , an exemplary workflow for a compare tool  330  is described in more detail. In the embodiment of  FIG. 4 , each record or document  315   a ,  315   b  has an associated identifier, DocumentID, as well as a data source identifier, DataSourceID, that identifies the data source from where the record or document  315   a ,  315   b  was retrieved. First, the compare tool generates a hash value, HashCode, for the current record or document  315   a ,  315   b . Next, the compare tool  330  compares the DataSourceID and DocumentID for the current record or document  315   a ,  315   b  to a table of data for previously entered records or documents  315   a ,  315   b  at block  402 . In the embodiment of  FIG. 4 , the table includes four items for each previously entered record or document  315   a ,  315   b : a 
     Field-to-field relation tables define the relationships between the fields in the entity tables. In one embodiment, three types of field-to-field relationships exist. A name-to-name relationship relates two name fields from two entity tables. A name-to-attribute relationship relates the name of one entity to an attribute of another entity. An exemplary field-to-field relationship is shown in  FIG. 2B . Finally, an attribute-to-attribute relationship relates the attribute of one entity to an attribute of another. Field-to-text relationships define the relationships between a fielded entity terms and the text of unstructured data. For example, the data model  140  may include a person table that defines people in the information space and a literature table that includes fields for various information about an article in the information space, but necessarily the text of the article. A text search of the article may be performed to determine if the person is mentioned in the article. An exemplary field-to-text relationship is shown in  FIG. 2C . In one embodiment, each of the field-to-field relationship tables and the field-to-text relationship tables includes a field for the primary key of each entity referenced as well as managerial data, such as a date created field. The relationship tables are described in more detail below in reference to  FIG. 5 . 
     Referring now to  FIG. 3 , an exemplary workflow for an extraction tool  120  in accordance with one embodiment is shown. Although the embodiment of  FIG. 3  shows certain processes being performed by certain exemplary tools and components, it should be apparent to one of ordinary skill in the art that functions discussed below could be performed by any of the tools or components. In one embodiment, a plurality of data sources  110  is provided. As stated above, each data source may contain thousands of data items of stored in various types of files—XML, flat-files, HTML, text, spreadsheets, presentations, diagrams, programming code, databases, etc.—that include information belonging to the given domain. In the embodiment of  FIG. 3 , each data source  110  may contain documents of any type, created at any point in time. It should be apparent to one of ordinary skill in the art that other repository structures are contemplated by the present invention. For example, one data source may be provided containing every piece of information to be analyzed. In other embodiments, a plurality of data sources may be provided where each data source may contain only documents of certain types, created at discrete segments of time, or created at a certain geographical locations. 
     The extraction tool  120  extracts relevant information from the various data sources  110 . Preferably, the extraction tool  120  is an asynchronous process that begins processing a file as soon as that file is retrieved from a data source  110 . Alternatively, the extraction tool  120  may be implemented as a batch process. In one embodiment, each data source has an associated data source type. In one embodiment, each data source may be either an internal data source or an external data source. An internal data source is a data source that is internal to the organization utilizing the knowledge discovery system  100 , whereas an external data source is a data source maintained by any other organization. Alternatively, or in addition to, the data source type may define the structure of the data source, such as the underlying directory structure of data source or the files contained therein. Additionally, the data source may be a simple data source consisting of a single directory, or a complex data source that may store metadata associated with each file kept in the data source. In one embodiment, the extraction tool  120  connects to each of the data sources  110  through data source adapters. An adapter acts as an Application Programming Interface, or API, to the repository. For complex data sources, the data source adapter may allow for the extraction of metadata associated with the information. 
     Exemplary data sources include PUBMED, a service of the National Library of Medicine that includes over 15 million citations for biomedical articles back to the 1950&#39;s, SWISS_PROT PROTEIN KNOWLEDGEBASE, which is an annotated protein sequence database established in 1986, the REFERENCE SEQUENCE (RefSeq) collection, which aims to provide a comprehensive, integrated, non-redundant set of sequences, including genomic DNA, transcript (RNA), and protein products, for major research organisms, KEGG, or the Kyoto Encyclopedia of Genes and Genomes, an ongoing project from Kyoto University, LOCUSLINK, a service of the National Library of Medicine that provides a single query interface to curated sequence and descriptive information about genetic loci, MESH, or Medical Subject Headings, the National Library of Medicine&#39;s controlled vocabulary thesaurus, OMIM, or Online Mendelian Inheritance in Man, a database catalog of human genes and genetic disorders, and NLM TAXONOMY, a searchable hierarchical index of names of all the organisms for which nucleotide or peptide sequences are to be found in certain data sources. Although each of these data sources constitutes a separate data source, the information in each data source has strong inter-relationships to information in others. Accordingly, the files stored in any particular data source  110  may include information relating the information therein. Referring to  FIG. 2B , for example, the PUBMED data source  110  may include information  260  relating a particular person to an organization. This information can be used to determine a relationship definition  266  for a particular person  262  and organization  264  in the knowledge model  140 . In one embodiment, a field-to-field relationship that has been determined from information obtained from a data source  110  is called a direct relationship. In one embodiment, all the field-to-field relationships are determined automatically using information from the data sources  110 . In further embodiments, a file may include information relating information in itself to information in other data sources  110 , or relating information in two separate data sources  110 . 
     Optionally, the extraction tool  120  may include various parameters used to determine whether a document is relevant. These parameters may be predefined or configurable by a user. For example, a user may configure the extraction tool to only extract files from specified directories. It should be apparent to one of ordinary skill in the art that many other relevance parameters—for example, only certain file types or only files that have changed after a certain date—are contemplated by the present invention. 
     As stated above, the extraction process  120  retrieves files from the data sources  110 . The original files may include large files that are of varying formats. In one embodiment, the extraction tool  120  includes a cut tool  310  that will split the original files into smaller records or documents  315   a ,  315   b , etc. Preferably, the cut tool  310  will process the original files such that each record or document  315   a ,  315   b  includes one and only one data item. Alternatively, the cut tool  310  may generate records or documents  315   a ,  315   b  that include more than one data item. The original files may also include the information about all items in a single file, separating the information using delimiters. Exemplary delimiters include “///” or a blank line. A configuration file may be provided that details the delimiters used at a particular source. The configuration file may be used by the cut tool  310  to process the original files. In one embodiment, the cut tool  310  may include particularized processor application for processing a particular type of original file, such as an XML processor for cutting XML files or a text processor for manipulating text files. In one embodiment, these particularized processor applications are implemented as C# objects using the C# object-oriented programming language from Microsoft Corporation of Redmond, Wash. 
     Once the files are split into records or documents  315   a ,  315   b , the extraction tool  120  preferably stores the records or documents  315   a ,  315   b  in a file system. Optionally, each record may include an identifier, such as an identifier used by the data source to identify the original file. Exemplary identifiers include a SWISS_PROT ID or a file name. Preferably, the extraction tool  120  also generates a global unique identifier for each record or document  315   a ,  315   b . The global unique identifier is used for tracking purposes, as described below. 
     The extraction tool  120  may also be provided with a map tool  320 . The map  320  functions to standardize the format of each record or document  315   a ,  315   b . In one embodiment, the map tool  320  serves two functions. First, the map tool  320  may create a normalized specification for the records or documents  315   a ,  315   b , such as a standardized XML specification. For example, records or documents  315   a ,  315   b  created from flat files may be transformed into xml files, while records or documents  315   a ,  315   b  created from XML files may be mapped to the standard XML specification. Second, the map tool  320  may remove information from the record or document  315   a ,  315   b  that is unnecessary to maintaining the knowledge model  140 . In one embodiment, the map tool  320  outputs a single text string of XML. 
     Next, the compare tool  330  of the extraction tool  120  compares the records or documents  315   a ,  315   b  with those records or documents  315   a ,  315   b  that have already been integrated into the knowledge model so that only records or documents  315   a ,  315   b  that are new are further processed. As used herein, a new record or document  315   a ,  315   b  includes records or documents  315   a ,  315   b  that have been integrated into the knowledge model  140 , but have since been modified. In other words, previously entered records or documents  315   a and  315   b  may include only those records or documents that have been integrated into the knowledge model  140  and have not changed since their integration. In one embodiment, compare tool  330  will compute a value based on the record or document  315   a ,  315   b . Preferably, the compare tool  330  uses a hash function to generate a hash value for each record or document  315   a ,  315   b . The value may be based on any part of the record or document  315   a ,  315   b , such as the identifier or the information contained therein. 
     Referring now to  FIG. 4 , an exemplary workflow for a compare tool  330  is described in more detail. In the embodiment of  FIG. 4 , each record or document  315   a ,  315   b  has an associated identifier, DocumentID, as well as a data source identifier, DataSourceID, that identifies the data source from where the record or document  315   a ,  315   b was retrieved. First, the compare tool generates a hash value, HashCode, for the current record or document  315   a ,  315   b . Next, the compare tool  330  compares the DataSourceID and DocumentID for the current record or document  315   a ,  315   b  to a table of data for previously entered records or documents  315   a ,  315   b  at block  402 . In the embodiment of  FIG. 4 , the table includes four items for each previously entered record or document  315   a ,  315   b : a DataSourceID that identifies the data source; a DocumentID that identifies the record or document  315   a ,  315   b ; a first hash code value, HashCodeActual, that represents the hash code value for that record or document  315   a ,  315   b  before it is integrated into the knowledge model  140 , and a second hash code value, HashCodeCompare, that represents the hash code value for that record or document  315   a ,  315   b  after it has been integrated into knowledge model  140 . If no match is found in the table, this record or document  315   a ,  315   b  has never been previously integrated into the knowledge model. Accordingly, the compare tool  330  stores the current DataSourceID and Document ID in the table at block  404 . Additionally, the HashCode will be stored as the HashCodeActual value for that record or document  315   a ,  315   b . The extraction process  120  will continue to process the record or document  315   a ,  315   b  at block  406 . Once the record or document  315   a ,  315   b  is integrated into the knowledge model  140 , the HashCodeCompare value will be updated with the HashCodeActual value at block  408 . 
     If a match is found in the table at block  402 , the record or document  315   a ,  315   b  has been previously integrated into the knowledge model  140 . The compare tool  330  next compares HashCodeActual to HashCodeCompare for the match. If two values are identical, the record or document  315   a ,  315   b  has not been modified since its last integration. Accordingly, the record or document  315   a ,  315   b  is not further processed as shown at block  412 . If the values are different, the record or document  315   a ,  315   b  has been modified since its last integration. In this case, the compare tool  330  updates the HashCodeActual value with the current HashCode value at block  414 . The extraction process  120  will continue to process the record or document  315   a ,  315   b  at block  416 . Once the record or document  315   a ,  315   b  is integrated into the knowledge model  140 , the HashCodeCompare value will be updated with the HashCodeActual value at block  418 . 
     At this point, the only records or documents  315   a ,  315   b  to be processed are new records or documents  315   a ,  315   b  that have been properly formatted. However, the information contained therein may contain unnecessary information as a consequence of different data sources using different nomenclatures. For example, an attribute name may be preceded by an asterisk or dash. Alternatively, the record or document  315   a ,  315   b  may contain HTML tag information. In one embodiment, the extraction process  120  is provided with a clean tool  340  that removes this unnecessary information from the records or documents  315   a ,  315   b.    
     Once the record or document  315   a ,  315   b  is cleaned, the parse tool  350  of the extraction tool  120  restructures the information of the record or document  315   a ,  315   b . For example, if a record or document  315   a ,  315   b  includes an XML attribute tag containing multiple values separated by a delimiter, the parse tool  350  may each value into separate tags. Additionally, the parse tool  350  may unifies the different nomenclatures of the records or documents  315   a ,  315   b  so that the information from the different sources is coherent. For example, an Organism name may be listed under a first label in one data source  110  and a second label  110  in another data source. The parse tool  350  may standardize this information. 
     Finally, the extraction process  120  may store the record or document  315   a ,  315   b  to be integrated into the knowledge model. In the embodiment of  FIG. 3 , the record or document  315   a ,  315   b  is stored in a database  360 . Alternatively, the record or document  315   a ,  315   b  may be stored in any manner that is apparent to one of ordinary skill in the art. In yet another embodiment, the record or document  315   a ,  315   b  is transmitted as part of a message to the integration process  130 . Preferably, the extraction tool  120  stores the record or document  315   a ,  315   b  in a database  260  and sends a message that alerts the integration tool  130  that a new record or document  315   a ,  315   b  has been inserted. In one embodiment, the message may be a field in the database  260  which is polled by the integration tool  130 . 
     Referring now to  FIG. 5 , an exemplary workflow for the integration process  130  is shown. Preferably, the integration process is an automatic, asynchronous process that doesn&#39;t need the entire extraction process  120  to finish. For example, in the embodiment of  FIG. 5 , the integration process  130  may begin integrating a record or document  315   a ,  315   b  as soon as it is inserted into the database  360 . This entry may be treated and integrated in an individual way and is passed through several components whose purpose is to integrate this source register into the knowledge model  140 . The integration tool  130  provides the users with more complete and higher quality information than the data sources  110  alone. 
     In the embodiment of  FIG. 5 , the integration tool  130  only processes new records or documents  315   a ,  315   b  because the extraction tool  120  has removed those records or documents  315   a ,  315   b  that have not been updated since the prior integration. This greatly improves the performance of the integration tool  130 , reducing the time necessary to complete the integration process. However, the integration tool  130  is equally capable of integrating any types of records or documents  315   a ,  315   b , regardless of whether they have been integrated previously. 
     In one embodiment, the integration tool  130  may receive information to integrate in three ways. First, the integration tool  130  may receive information from the extraction tool  120 . For example, the extraction tool  120  may process a record or document  315   a ,  315   b  from a data source, insert the record or document  315   a ,  315   b  into a database  360 , and alert the integration tool  130  of the presence of the new information. In response, the integration tool  130  may retrieve the information from the database  360 . Second, the integration tool  130  may receive information from a re-integration batch process. The re-integration batch process may build a message (of a similar format to those generated by the extraction process  130 ) that alerts the integration process  130  to the presence of a record or document  315   a ,  315   b  that could not be integrated into the knowledge model  140  during a previous attempt. Finally, custom applications may be developed to alert the integration tool  130  of information from particular data sources  110  that do not require the full functionality of the extraction tool  120 . For example, an internal data source  110  may be provided that includes files that adhere to a particular structure designed to ease the integration process. It should be apparent to one of ordinary skill in the art that any method may be used to introduce a record or document  315   a ,  315   b  to the integration tool  130 . 
     The integration tool  130  may be provided with an integrate tool  500 . The integrate tool  500  performs four primary processes. First, the integrate tool may retrieve a record or document  315   a ,  315   b  from the database  360 . Next, the integrate tool  500  may perform a spell check function  510  on the data included in the record or document  315   a ,  315   b  to ensure that misspellings in the original data source  110  files do not effect the integrity of the knowledge model  140 . Similarly, the integrate tool  500  may perform a synonym function  520  to determine if the current term (as used in the record or document  315   a ,  315   b ) is a synonym for a preferred name. Finally, the integrate tool  500  may perform a merge function  530  that integrates the record or document  315   a ,  315   b  into a database  540 . In one embodiment, the database  540  represents a un-optimized version of the knowledge model  140 . A particular embodiment of the integrate tool  500  is discussed in more detail below in reference to  FIGS. 9-13 . 
     The integration tool  130  may also be provided with various batch-process tools to perform various functions on the information in the database  540 . In the embodiment of  FIG. 5 , the integration tool  130  includes a relationship generation tool  550  that may be used to analyze the information in the database  540 . The relationship generation tool  550  is discussed in more detail below in reference to  FIG. 14 . Similarly, a synonym synchronization tool  560  may run periodically to update the information in the database  540  in accordance with the most recent list of synonyms. Finally, a transition tool  570  may be provided to optimize the information in the database  540  to create the knowledge model  140 . For example, the transition tool  570  may denormalize the information in the database  540 , generate cross-over tables, build indices on clustered indices on the primary key columns of various tables of the database  540 , and optimize the database  540  for queries and data retrieval tasks. In one embodiment, the transition tool  570  generates a database  580  that is replicated in a production environment as the knowledge model  140 . 
     Referring now to  FIG. 6 , the workflow for one embodiment of the integrate tool  500  is shown. As described above, the extraction tool  120  may send a message to the integrate tool  130  to inform the integration tool  130  that new entries in the database  360  need to be integrated into the knowledge model  140 . The message may also indicate that the entries are from a particular data source  110 . Initially, the integrate tool  500  creates an XMLDocument object. The XMLDocument object is a working version of a standard configuration file. In one embodiment, each data source has a standard configuration file in XML that acts as template for the integration tool  130 . An exemplary configuration file is shown in Table 1. It should be apparent to one of ordinary skill in the art that various types of configuration files in other formats are contemplated by the present invention. 
     
       
         
           
               
             
               
                 TABLE 1 
               
               
                   
               
               
                 Sample XML Data Source Configuration File 
               
               
                   
               
             
            
               
                   
               
            
           
           
               
               
            
               
                   
                 &lt;DataSource Name=”DataSourceName”&gt; 
               
               
                   
                   &lt;SDB1Table Name=”SDB1TableName”&gt; 
               
               
                   
                     &lt;Thesaurus&gt; 
               
               
                   
                       &lt;SDB1FieldThesaurus Name=”FieldName” 
               
               
                   
                       ThesaurusSP=”ThesaurusSPName” SpellingSP 
               
               
                   
                       =”SpellingSPName” /&gt; 
               
               
                   
                       ... 
               
               
                   
                     &lt;/Thesaurus&gt; 
               
               
                   
                     &lt;LookUp SPName=”SPName”&gt; 
               
               
                   
                       &lt; SDB1FieldLookUp Name=”SDB1FieldName” 
               
               
                   
                       GetIDSP=”SPGetID”/&gt; 
               
               
                   
                       ... 
               
               
                   
                     &lt;/LookUp&gt; 
               
               
                   
                     &lt;Compare&gt; 
               
               
                   
                       &lt;SDB1FieldCompare Name=”SDB1FieldName” 
               
               
                   
                       MDB1Field=”MDB1FieldName”&gt; 
               
               
                   
                       ... 
               
               
                   
                     &lt;/Compare&gt; 
               
               
                   
                     &lt;Insert SPName=”StoredProcToInsert”&gt; 
               
               
                   
                       &lt;SDB1FieldInsert Name=”SDB1FieldName” 
               
               
                   
                       ConfidenceValue=”ConfidenceValue”/&gt; 
               
               
                   
                       ... 
               
               
                   
                     &lt;/Insert&gt; 
               
               
                   
                     &lt;Update SPName=”StoredProcToInsert”&gt; 
               
               
                   
                       &lt;SDB1FieldUpdate Name=”SDB1FieldName” 
               
               
                   
                       ConfidenceValue=”ConfidenceValue” 
               
               
                   
                       Type=”U/A” DB1FieldName=”MDBFieldName” 
               
               
                   
                       MDB1ConfidenceValue=”MDB1ConfidenceField 
               
               
                   
                       Name”/&gt; 
               
               
                   
                       ... 
               
               
                   
                     &lt;/Update&gt; 
               
               
                   
                   &lt;/ SDB1Table &gt; 
               
               
                   
                   ... 
               
               
                   
                 &lt;/DataSource&gt; 
               
               
                   
                   
               
            
           
         
       
     
     As shown, the configuration file includes various attributes that are used in later stages of the integration process. The exemplary configuration file includes five attributes, a Thesaurus attribute, a LookUp attribute, a Compare attribute, an Insert attribute, and an Update attribute. The thesaurus attribute includes information in the record that need to be checked for spelling and/or synonyms. In particular, the thesaurus attributes define a field name to be checked and the values for that field name. This value will appear in ThesaurusSP and SpellingSP attributes if the value needs to be checked for synonyms or spelling, respectively. If both the value needs to be checked for both spelling and synonyms, it will appear in both attributes. The LookUp attribute defines each field in the database  360  and the name of a procedure that can be used to lookup the associated row in the knowledge model  140 . The Compare attribute defines the field in the database  360  and its corresponding field in the knowledge model  140 . The Insert attribute defines each field in the database  360  and its corresponding confidence value, as described below. Finally, the Update attribute defines each field in the database  360 , its corresponding confidence level, the field type, and the corresponding field in the knowledge model  140  and its corresponding confidence value. In one embodiment, two field types are defined. An update type implies that the value of the field should be replaced in its entirety if a new record or document  315   a ,  315   b  is to replace an existing entry in the knowledge model  140 . An append type implies that the information in the new record or document  315   a ,  315   b  should be appended to the current information. 
     As stated above, each field includes an associated confidence value. The confidence value is used score the reliability of the data sources  110  for each field of the knowledge model  140 . For example, multiple data sources  110  may include information for one field of the knowledge model  140 . To resolve this conflict, the confidence value is used to determine which data source is more reliable for a given field. The confidence value may reflect an internal view of the reliability of the data sources  110  (i.e. the view of the system developers or the organization utilizing the knowledge discovery system  100 ) or may reflect an external view of reliability (i.e. the use of a third party reliability standard). In one embodiment, the confidence value is a numerical value from 1-20 where the confidence value increases with the reliability of the data source  110 . In one embodiment, each of the plurality of data sources  110  is ranked from 1 to N for each field of the knowledge model, where N is the number of data sources  110 . Alternatively, multiple data sources  110  may be equally reliable and therefore have the same confidence value. In such an embodiment, the integration tool  130  may chose the most recent record or document  315   a ,  315   b  as controlling. Alternatively, the integration tool  130  may only replace a field if the confidence value of the new record or document  315   a ,  315   b  is greater than the current entry. 
     In one embodiment, a confidence value configuration file is provided. The confidence value configuration file may define a confidence value for each field of the knowledge model  140  and for all data sources  110 . Alternatively, a separate confidence value configuration file may be provided for each data source  110 . It should be apparent to one of ordinary skill in the art, that various ways of tracking the reliability of a data source  110 , as well as various types of configuration files, are contemplated herein. An exemplary XML confidence value configuration file is shown in table 2. In the exemplary confidence value configuration file, each field of each table from each data source  110  is ranked. 
     
       
         
           
               
             
               
                 TABLE 2 
               
               
                   
               
               
                 Sample XML Confidence Value Configuration File 
               
               
                   
               
             
            
               
                   
               
            
           
           
               
               
            
               
                   
                 &lt;Table&gt; 
               
               
                   
                   &lt;DataSource1&gt; 
               
               
                   
                     &lt;field1&gt; ConfidenceValue &lt;/field1&gt; 
               
               
                   
                       ... 
               
               
                   
                     &lt;fieldn) ConfidenceValue &lt;/fieldn&gt; 
               
               
                   
                   &lt;/DataSource1&gt; 
               
               
                   
                   ... 
               
               
                   
                 &lt;/Table&gt; 
               
               
                   
                   
               
            
           
         
       
     
     Referring now to  FIG. 7 , an exemplary workflow for the loading the information from a received message into an XMLDocument object is shown. First, the integrate tool  500  reads the configuration file for the data source identified in the message at block  702 . Next, a check is performed to determine if an XMLDocument object for this data source is cached at block  704 . If so, the XMLDocument object is retrieved from the cache at block  706 , and the information from the message is used to populate the ConfigFileContent property of the XMLDocument at block  708 . If no XMLDocument object for the particular data source is in the cache, the integrate tool  500  will create a new XMLDocument object and load it with the configuration file information at block  710 , put the new XMLDocument in the cache at block  712 , and populate the ConfigFileContent property of the XMLDocument with the information from the message at block  708 . 
     Returning to  FIG. 6 , after loading the received message into an XMLDocument object at  602 , the integrate tool  500  next checks to see if the message contains a record or document  315   a ,  315   b  that needs to be integrated into the knowledge model at block  604 . If the message does not contain any additional records or documents  315   a ,  315   b  that need to be integrated, the process ends at block  606 . If the message does contain a record or document  315   a ,  315   b  that needs to be integrated, the integrate method retrieves that record or document  315   a ,  315   b  from the database  360  at block  608 . Next, the integrate tool  500  calls the thesaurus component to perform the spelling function  510  and synonym function  520  at block  610 . In the embodiment of  FIG. 6 , the thesaurus component includes an internal source, such as a database, with containing information on commonly misspelled words and synonyms or preferred words. In either case, the thesaurus component will replace the misspelled or non-preferred word with the proper word. Alternatively, an external source may be used by the thesaurus component. 
     Referring to  FIG. 8 , an exemplary workflow for the Thesaurus component is shown. First, the Thesaurus component retrieves the field names from the XMLDocument Thesaurus attribute at block  802 . Next, the Thesaurus component will check to determine if any more fields need to be checked at block  804 . If no more fields need to be checked, the Thesaurus component will exit at block  806 . If a field needs processing, the Thesaurus component will retrieve the corresponding ThesaurusSP and SpellingSp values at block  808 . Next, the Thesaurus component will retrieve the word to check at block  810 , and call the SpellingCheck procedure at block  812 . The SpellingCheck procedure first determines if the SpellingSp value is non-blank at block  814 . If the SpellingSp value is non-blank, the SpellingSP procedure is executed at block  816 . In one embodiment, the SpellingSp procedure checks the SpellingSp value against a spellings table that includes the correct word and various misspellings. When the correct word is found, it is substituted for the old value at block  818 . At this point, or if the SpellingSp value is determined to be blank at block  814 , the Thesaurus component moves on to the ThesaurusCheck procedure at block  820 . Similar to the SpellingSp procedure, the ThesaurusCheck procedure first determines if the ThesaurusSP value is non-blank at block  822 . If the ThesaurusSP value is non-blank, the ThesaurusSP procedure is executed at block  824 . In one embodiment, the ThesaurusSP procedure checks the ThesaurusSP value against synonym table that includes a preferred word and various synonyms. When the correct word is found, it is substituted for the old value at block  824 . The Thesaurus component then returns to block  804  to determine if any additional fields need to be checked, and continues to loop until all the fields have been processed. 
     Returning to  FIG. 6 , once the Thesaurus component has finished, the record or document  315   a ,  315   b  is passed to the Merge component at block  612 . In order to make the knowledge model  140  a richer source of information than any one underlying data source  110 , the knowledge model  140  typically includes more information on a given entity than any single data source  110 . The Merge component is used to update the knowledge model  140  with the new records or documents  315   a ,  315   b  stored in the database  360  and assimilate the various pieces of information from the various data sources  110 . In one embodiment, the Merge component takes a single record or document  315   a ,  315   b  and uses it to fill a single row in the database  540 . First, the Merge component has to determine if the information provided by the record or document  315   a ,  315   b  complements the existing information or it represents new information. Depending on the comparison, the record or document  315   a ,  315   b  is either inserted into the database  540  as a new row or used to update the contents of an existing row. In one embodiment, four tools are used to accomplish these tasks. First, the Merge component may include a LookUp component that is used to determine if the record or document  315   a ,  315   b  can be integrated into the knowledge model and if the record or document  315   a ,  315   b  is entirely new, for example, if there is now row in the database  540  that corresponds to this record or document  315   a ,  315   b . If a row exists that corresponds to this record or document  315   a ,  315   b , the Merge component may utilize a Compare component to determine if the existing row in the database  540  includes null values in the fields to be modified by the record or document  315   a ,  315   b  to be processed. If not, a new row may be added to the database  540 . If the row does include null values, that information must be updated with the information in the record or document  315   a ,  315   b . Depending on the results of these tests, an Insert component may be used to add a new row or an Update component may be used to update a row. 
     Referring now to  FIG. 9 , an exemplary workflow for an embodiment of the Merge component is shown. First, the Merge component calls the LookUp component at block  902 , which determines if the record or document  315   a ,  315   b  can be integrated at block  904 . If the record or document  315   a ,  315   b  cannot be integrated, the Merge component returns this information to the integrate tool  500  at block  906  and exits at block  908 . If the record or document  315   a ,  315   b  can be integrated, the LookUp component then determines if the record exists at block  910 . If not, the record or document  315   a ,  315   b  is then passed to the Insert component at block  912 , and the Merge component ends at block  908 . If the record does exist, the Compare component is called to determine if the record exists with null information at block  916 . If the record does not include null information, the record or document  315   a ,  315   b  is passed to the Insert component at block  912  and the Merge component exits at block  908 . If the record does not include null information, the record or document  315   a ,  315   b  is passed to the Compare component at block  918  and the Merge component exits at block  908 . 
     Referring now to  FIG. 10 , an exemplary workflow for an embodiment of the LookUp component is shown. First, the LookUp component retrieves the StoredProcedure attribute from the XMLDocument object, as described above, at block  1002 . Next, the LookUp component retrieves the first field information from the database  360  which need to be checked at block  1004 . At block  1006 , the LookUp component determines if any additional fields need to be processed. If so, the LookUp component compiles a dataset of all the values that need to be looked up. To do this, the LookUp component retrieves the additional field from the value at blocks  1008  and  1010 , and determines the corresponding table in the database  540  for this field at block  1012 . If the value is not found in the database  540 , the LookUp component performs a lookup function on the value for the fields at block  1016  and determines if the ID for that value is found at block  1018 . If the ID is not found, the LookUp component checks the record to be re-integrated later at block  1020 , informs the integrate tool  500  that the record could not be integrated at block  1020 , and exits at block  1024 . If the ID is found, the LookUp component will return to block  1006  and continue compiling the list of fields to look up. Once there are no additional fields to look up, the LookUp component determines if the records exist at block  1022  and exits at block  1024 . 
     Referring now to  FIG. 11 , an exemplary workflow for the Compare component is shown. First, the Compare component retrieves the XMLDocument Compare attribute at block  1102 . Next, the Compare component compiles a dataset of all the values in the record that need to be compared at blocks  1104 ,  1106  and  1108 . Once this dataset is compiled, the Compare component determines if any values in this dataset are included in the dataset determined by the LookUp component at block  1110 . If so, those records are returned to the Update component, as described above, at block  1114  and exits at block  1116 . If the values are not the same, the Compare component then determines if the values are null. If so, those records are returned to the Update component, as described above, at block  1114  and exits at block  1116 . If the values are not null, the Compare component exits at block  1116 . 
     Referring to  FIG. 12 , an exemplary workflow for an Insert component is shown. First, the Insert component retrieves the stored procedure name that performs the actual inserts at block  1202 . Next, the Insert component retrieves the field values and confidence levels from the XMLDocument object, as well as the values from the database  360  for the record to be inserted at block  1204 . Using this information, the Insert component builds a call to the stored procedure to insert the new information at block  1206 . Finally, the call is executed at block  1208 . 
     Referring now to  FIG. 13 , an exemplary workflow for an Update component is shown. First, the Update component retrieves the name of the stored procedure that performs the actual update at block  1302 . Next, it reads the Update attribute from the XMLDocument object at block  1304 . A check is performed to determine if there any more fields in the Update attribute that need to be processed at  1306 . If so, the Update component retrieves the field value and corresponding confidence level from record or document  315   a ,  315   b  at blocks  1314  and  1316 , respectively. It then retrieves the confidence level of the current entry in the knowledge model  140 , and compares the two confidence values at block  1320 . If the confidence value for the new field is greater than the current confidence value, the new field is marked to ‘Update’, meaning that this new value should replace the existing value, at block  1322 . If the current confidence value is greater than the new confidence value, however, the current value will not be overwritten. The Update component continues in this manner until all of the update fields have been processed. When there are no additional fields to process, the Update component builds the procedure call at block  1308 , executes the call at block  1310 , and exits at block  1312 . 
     Returning to  FIG. 6 , once the Merge component has finished processing the records or documents  315   a ,  315   b  from the message, a check is made to determine the result at block  614 . If the process was successful, the record or document is removed from the database  360  at block  616 , and the integrate tool  500  returns to block  604  to process the next record in the message. Alternatively, if the Merge component was unsuccessful, the age field for the record is incremented at block  618 , and the integrate tool  500  returns to block  604  to process the next record in the message. The concept of “age” appears as a result of the automatic, asynchronous nature of the integration process. For example, as described above, the merge component can be used to merge entities or relationships. A potential problem could arise if the system attempts to merge a relationship before one of entities of the relationships exists in the knowledge model  140 , such as a relationship that defines a relation between entities a and b before entity b exists in the knowledge model  140 . The re-integration batch process described above may be used to reintroduce these records or documents  315   a ,  315   b  at a later time. In one embodiment, the records or documents  315   a ,  315   b  may be deleted if their ‘age’ reaches a particular level, for example, 10. Alternatively, or in addition to, either the integration or re-integration process may determine if a record or document  315   a ,  315   b  covering the same field and from the same data source  110  has been integrated subsequently. If so, the integration of the ‘old’ record or document  315   a ,  315   b  is no longer necessary, and it may be deleted. 
     Referring now to  FIG. 14 , an exemplary relationship generation tool  550  is shown. As discussed above, the relationship generation too may be used to analyze the information in the knowledge model  140  and populate various relationship tables. In the embodiment of  FIG. 14 , the relationship generation tool  550  includes three components. The field-to-text relationship tool  1410  generates the field-to-text relationships, as described above. In one embodiment, the field-to-text relationship tool  1410  reads each name field from every entity table. For each name field, the field-to-text relationship tool  1410  executes a stored procedure that searches for the given name in various other fields of the entity tables. For example and with reference to  FIGS. 2A and 2C , the field-to-text relationship tool  1410  may select the name field from person entity table and search for that entry in the title and abstract fields of the literature entity table. If a match is found, a field-to-text relationship may be added to the field-to-text relationship table. Alternatively, or in addition to, the field-to-text relationship tool  1410  may retrieve the full text of the article referenced by the literature table (even though the article is not necessarily stored in the knowledge model  140 ) and perform a similar search. It should be apparent to one of ordinary skill in the art that the field-to-text relationship tool  1410  may be configured to select any set of fields from the entity tables and search any other fields in the entity tables. Additionally, the field-to-text relationship tool  1410  may be configured to search the text of unstructured data that is not referenced in any entity in the knowledge model. 
     The relationship generation tool  550  may also be configured to derive relationships by analyzing the data of the knowledge model  140 . These types of relationships are referred to herein as derived relationships. In one embodiment, the relationship generation tool may include a transitive relationship tool  1420 . The transitive relationship tool  1420  determines transitive relationships. As used herein, a transitive relationship is defined as any relationship between two entities that is based on at least two separate relationships. As discussed above, a direct relationship is a relationship that has been determined from information in a data source  110 . These direct relationships may be stored in a direct relationship table. In one embodiment, the transitive relationship tool  1420  selects each row in the direct relationship table. For each field referred to in the relationship definition, the transitive relationship tool  1420  may search every other row in the direct relationship table for a match. If a match is found, a new relationship is created to reflect the commonality. For example, if a direct relationship is defined between field A and field B, the transitive relationship tool  1420  may search the other rows of the direct relationship table for a match on field A. If a match is found, for example, relating field A to field C, the transitive relationship tool  1420  may create a transitive relationship relating field B to field C. This is an example of a single hop transitive relationship. Preferably, the transitive relationship tool  1420  uses a search depth algorithm to calculate the transitive relationships across n hops. In one embodiment, the transitive relationship may be stored in a transitive relationship table. Alternatively, the transitive relationship may be stored in the same table as the direct relationships. In one embodiment, the transitive relationship definition includes information detailing each hop from the two related entities. 
     The relationship generation tool  550  may also include a proximity relationship tool  1430 . Similar to the field-to-text relationship tool  1410 , the proximity relationship tool  1430  searched the text of either fields in the knowledge model  140  or unstructured files, such as articles. The proximity relationship tool  1430  creates a proximity relationship if two entities appear in the same text. In one embodiment, indexes are created for all the text to be searched (i.e. specific field values or unstructured data items). The indexes are then used to determine if two entities appear in the same text. Alternatively, or in addition to, the proximity relationship tool  1430  may be configured to generate a proximity relationship if the entities appear within a given proximity of each other in the text, for example, within n words of each other. Other criteria, such as each field appearing at multiple instances within each document, each field appearing in the same sentence, and the like, may also be used to define a proximity relationship. It should be apparent to one of ordinary skill in the art that the determination of a proximity relationship may be dependent on the type of file being examined. For example, if a text file is be used, a proximity relationship may be generated if the words fields appear within the same paragraph. If, however, the file being searched is a spreadsheet, the proximity relationship tool  1430  may generate a proximity relationship if the two fields appear in same cell, row, or column. In one embodiment, the proximity relationship tool  1430  stores the proximity relationship definition as well as information detailing the rationale behind the generation of the relationship. For example, to define a proximity relationship between two fields, the proximity relationship tool  1430  may store each field, the criteria used to determine the relationship, and the article or reference in which the use of the fields met the given criteria. 
     Referring to  FIGS. 15-26 , an exemplary navigator tool  170  is shown. In the embodiment of  FIGS. 15-26 , the navigator tool  170  is a graphical user interface that allows the user to select a record or item from one of a table of the knowledge model  140  and, in response to the selection, display a set of related items or records. Preferably, and only registered users may access the knowledge model  140 . It should be apparent to one of ordinary skill in the art that other implementations of the navigator tool  170  are contemplated herein. In one embodiment, the user may be initially directed to a log in to the navigator tool  170  in order to access the data stored in the knowledge model  140 . To do so, the user may enter a valid username and password combination. The user may then submit this information to be validated against a database of user information, for example, the user information database  145 . Optionally, the user may be allowed to select an option to store the username and password information for future log in attempts. 
     In the embodiment of  FIGS. 15-26 , the navigator tool  170  includes a toolbar  1510  and a navigation area  1520 . The toolbar  1510  may provide access to a variety of functions of the navigator tool  170  via corresponding interface objects, such as a navigation functions. The toolbar and various capabilities accessible via the toolbar are described in more detail below in reference to  FIGS. 19-26 . In one embodiment, the navigation area  1520  includes nine visually separated panels  1530 . Each panel  1530  contains information corresponding to an entity of the knowledge model  140 . The information contained in each panel may be referred to as an Item. The Item in the center, or active, panel  1530  may display a single Item. Each of the remaining panels  1530  may display zero, one or more Items for a particular entity table of the knowledge model  140  that relate to the Item in active panel  1530 . 
     Referring now to  FIGS. 16 and 17 , a diagram of exemplary components and an exemplary layout for one embodiment of a navigation tool  170  are shown, respectively. The Navigator component  1602 ,  1702  is the main component that will contain the rest of the components and manage the interface among all the other components of the navigator tool  170 . In one embodiment, each Navigator component  1602 ,  1702  comprises a ToolTipPanel component  1604 ,  1704 , one to nine EntityPanel components  1606 ,  1706 , one or more RelationLine components  1620 ,  1720 , and an Information Panel component  1622 ,  1722 . 
     The ToolTipPanel component  1604 ,  1704  may include summary and supporting attribute information about an Item. In one embodiment, ToolTipPanel components  1604 ,  1704  are implemented as pop-up boxes that appear when a user mouses-over an Item. For example, a ToolTipPanel component  1604 ,  1704  for an Item describing a person might contain their age, level within their company, hire date, email address, and the like. In one embodiment, the ToolTipPanel component  1604 ,  1704  associated with the active Item may be permanently displayed below the Item name. 
     The EntityPanel component  1606 ,  1706  includes information corresponding to an entity of the knowledge model  140 . In the embodiment of  FIGS. 16 and 17 , each EntityPanel component  1606 ,  1706  consists of a TitleBar component  1608 ,  1708  and a body component  1610 ,  1710 . The TitleBar component  1608 ,  1708  may include information about the entity, such as an entity name, icon for the entity. The Body component  1610 ,  1710  may include information about the Items in an entity table. In one embodiment, the Body component  1610 ,  1710  includes one or more EntityItem components  1614  and a DataList component  1616 . Each EntityItem component  1614 ,  1712  includes information for an item being displayed in the EntityPanel component  1606 ,  1706 . Optionally, the TitleBar component  1608 ,  1708  may include node counter information that shows how many Items from the particular entity table are related to the Item in the active panel  1606 ,  1706  as well as which items are currently visible. In one embodiment, both the EntityItem components  1614 ,  1714  and TitleBar components  1608 ,  1708  may be associated with a PopUpMenu components  1612 ,  1712  which provide access to various functions associated with the the EntityItem components  1614 ,  1714  and TitleBar components  1612 ,  1712 , respectively. 
     Referring now to  FIG. 18A-D , an exemplary screen shot of a navigator tool  170  is shown. The navigator tool  170  may include a toolbar  1810  and a navigator component  1820 . In the embodiment of  FIG. 18 , the navigator component  1820  includes the elements described above in regard to  FIGS. 16 and 17 . As shown, the navigator component  1820  includes nine entity components  1830 , each including a title component  1834  and a body component  1836 . The title component  1834  includes the name of an entity table and, where applicable, a node counter that displays the total number of items  1840  included in the corresponding entity components  1830 . 
     As described above, the navigator tool  170  may be implemented as a graphical user interface that allows the user to select a record or item from one of a table of the knowledge model  140  and, in response to the selection, display a set of related items or records. In the embodiment of  FIG. 18  the center entity component  1832  represents the active or selected node  1838  and includes the name of the active node  1838 . In one embodiment, the name of active node  1838  may be truncated. Optionally, the navigator tool  170  may be configured to display a pop-up window displaying various information about the active item  1838  upon a predetermined event, such as an activation of the item  1838  via a single-click, double-click, mouse-over, and the like. Optionally, the same functionality may be provided for the related nodes  1840 . 
     The remaining entity components  1832  may be used to display those related items  1840  in the knowledge model  140  related to the active node  1838 , for example, by displaying the name of the related item  1840 . Optionally, indicia of the link type associating each related item  1840  to the active node  1838  may be included. In the embodiment of  FIG. 18 , a roman numeral indicating the type of link is used to indicate the link type. For example, direct, or field-to-field, links may be designated by the roman numeral “I”, field-to-text links by the roman numeral “II”, transitive links by the roman numeral “III,” and proximity links by the roman numeral “IV.” Other exemplary indicia may include using associated font colors, font sizes, or any other visual indicator. In one embodiment, the navigator tool  170  may query the knowledge model  140  to determine the related items  1840  in response to the selection of the active node  1838 . Preferably, queries are performed via a batch process that determines all related items  1840  for each item  1830  of the knowledge model. The queries may be saved, for example in a database table, to vastly improve the performance of the navigator tool  170 . 
     Each entity component  1832  is associated with a particular table of the knowledge model  140 . In one embodiment, each entity component  1832  displays all the related items  1840  for the associated table of the knowledge model  140 . Preferably, the user will be allowed to select the type of entity being displayed in any particular entity component  1832  by associating that entity component  1832  to any table in the knowledge model  140 . In such an embodiment, the user may configure the entity components  1832  to display the tables of interest to that particular user. Preferably, the associations of entity components to knowledge model  140  tables may be stored. 
     In one embodiment, each entity component  1832  may be configured to display a set number of item  1840  at a given time. In such an embodiment, navigation tools, such as a scroll bar or navigation arrows, may be provided to allow the user to access the entire list of related items  1840 . Additionally, the entity component  1832  may include node  1840  count information to inform the user of the additional though not visible items  1840 . Preferably, the entity component  1832  also includes information describing which related items  1840  of the set are currently being displayed. For example, the entity component  1832  may show that items  1840  three through nine of eighty-six total items  1840  are currently being displayed. In such an embodiment, a scrollbar or other user-interface control may be included to provide access to the items  1840  not being displayed. 
     Optionally, the entity component  1832  may include tools to manipulate the related items  1840  contained therein. In the embodiment of  FIG. 18A , each entity component includes a sort button  1842 . The user may activate the sort button  1842  to sort the list of related items  1840  alphabetically or by confidence level. Other criteria such as date restrictions and the like may also be used to sort the related items  1840 . The entity component may also include a filters button  1844  which opens the master filters dialog for the corresponding entity, described in more detail below in reference to  FIGS. 26A-E . 
     As described above, each entity component  1832  may be associated with an entity type of the knowledge model  140 . In one embodiment, the user may change the entity table associated with any entity component  1832  that displays related items  1840 . As shown in  FIG. 18B , the user may activate a menu, that includes a list of all possible entity tables of the knowledge model  140  that may be associated with the particular entity component  1832 . This menu may be activated, for example, by selecting the appropriate triangle icon  1848  on the title component  1834 . Other methods of changing the associations between an entity components  1832  and entity tables of the knowledge model  140  are contemplated herein. 
     In one embodiment, the activation of a particular related item  1840  may cause additional information about that item  1840  and its relationship to the active item  1838  to be displayed. As shown in  FIG. 18C , the selection of a related item  1840  may cause a ToolTipPanel component  1850  to be displayed that shows summary information for the related item  1840 . 
     Additionally, or alternatively, a relationship line  1852  between the related item  1840  and the active item  1838  may also be displayed upon activation of the related item  1840 . In the embodiment of  FIG. 18C , the color and style of the relationship line  1852  indicates the type of relationship between the two items. For example, a continuous green line may indicate a field-to-field link, a dashed blue line may indicate a field-to-text link, a dashed and dotted yellow line may indicate a transitive relationship, and a dotted red line may indicate a proximity relationship. It should be readily apparent to one of ordinary skill in the art that the relationship type may be indicated using color, style, size, and the like, or any combination therein. 
     As shown in  FIG. 18D , the user may select any of the related items  1840  to make that item the active node  1838 . In response, the navigator tool  170  may update the display accordingly. In one embodiment, the navigator tool  170  may submit a new query or retrieve saved queries from the knowledge model  140  and display the related items  1840  to the new active item  1838 . Alternatively, or in addition to, the user may drag-and-drop a related item into the center entity panel to make that item the active item  1838 . 
     As shown in  FIG. 18E , the user may access a variety of item-related options via a pop-up menu  1854 , for example, by right clicking on an item. In one embodiment, the pop-up menu  1852  provides access to functions create a bookmark to an item, make an item the home item, email a link to an item, monitor an item, and show link evidence for a related item  1840 . A bookmark is a link to a particular item. Bookmarks are stored in a list of bookmarks accessible via the bookmark button of the navigator toolbar  1810 , described in more detail below. The home item is a special bookmark that can be loaded into the navigator tool by pressing the home button of the navigator toolbar  1810 . Items may be emailed to an individual by selecting the email link option. In one embodiment, selecting the email link option launches the default mail program, creates a new e-mail with a system generated introduction, and places the link to the item into the new e-mail message. Additionally, the user may select an item to monitor via the pop-up menu. As described in more detail below, the system  100  may monitor items and notify the user of updates and/or changes to the items. When a user denotes an item to monitor, a date stamp may be created and saved with item information to be used by the system  100  for monitoring. 
     Finally, the user may wish to see information on why a particular related item  1840  is considered related to the active node  1838 . To do so, the user may select the show link evidence option from the pop-up menu  1854 . Depending on the type of link establishing a connection between the active node  1838  and the related node  1840 , different link information may be shown. For example, link information for field-to-field links may include the data source from which the link was extracted. Link information for field-to-text links may include a short part or clip of the literature text that surrounds the keyword. In one embodiment, the clip length should user configurable. Preferably, the clip length may be initially set to be N words total, such that (N−1)/2 words preceding the item keyword and (N−1)/2 words following the item keyword are included. For example, if the clip is set to 31 words, the clip may include the 15 words preceding and following the item keyword. For transitive links, the link information may include each field-to-field link information for each hop included in the link. Finally, link information for proximity links may include the title of the article which mentions both items, as well as a clip for showing each item in context. 
     As described above, the navigator tool  170  may include a navigation toolbar  1810 . One embodiment of the navigation toolbar  1810  is shown in  FIG. 19 . The navigation toolbar  1510  may contain icons and controls which enable the user to access and configure the various services of the navigator tool  170 . In one embodiment, the navigation toolbar  1510  may include a back button  1910 , a forward button  1912 , a stop button  1914 , a refresh button  1916 , a home button  1918 , a history button  1920 , a signoff button  1922 , a help button  1924 , an about button  1926 , a search button  1928 , a wizards button  1930 , a bookmarks button  1932 , a monitored items button  1934 , a filters button  1936 , a source filters drop-down list  1936 , a confidence level tool  1940 , a context drop down list  1942 , and an options button  1944 . It should be apparent to one of ordinary skill in the art that the various user interface components may be used provide access to the functions described below. 
     The navigation tool  170  provides basic navigational functions via the navigation buttons. For example, the back button  1910  and forward button  1912  may be provided to allow the user to step through their recent navigation history backwards and forwardly, respectively. Activating the stop button  1914  may cancel the submission of a query to the knowledge model  140 . In one embodiment, a command is issued to the knowledge model  140  to abort query processing. Preferably, all current client and server processing activity is stopped. Activating the refresh button  1916  may allow the user to manually refresh their current view (for example, by resending a query to the knowledge model  140 ) and update the display of related item  1840  based on the new results. A home button  1918  may be provided that takes the user to their home view (i.e. home item). The home view is a set node. The home view may be user customizable. 
     A history dialog button  1920  may also be provided to launch a history dialog window. One embodiment of a history dialogue window is shown in  FIG. 20 . The dialog window  2000  may show the user&#39;s recent navigation history, such as a list of navigation events  2010 . In one embodiment, both the node name and entity name are displayed. The user may be able to highlight a navigation event and click a “show” button  2020  to refocus the navigator  170  on that item by making that item the active node  1838 . Alternatively, or in addition to, the user may be able to double-click on a history item and refocus the navigator on that item. The user may close the history dialogue window  2000  by selecting the close button  2030 . In one embodiment, the navigator tool  170  may save a set number of history events. This number may be user-configurable. Preferably, the history events may be stored in the user information database  145  to make the history events session independent and persistent. 
     Upon selection of the signoff button  1922 , the user may be logged out of the navigator tool  170 . Upon selection of the help button  1924 , the user may be provided access to a help system, as known in the art. In one embodiment, selection of the help button  1924  may cause an html based help system to be launched in a separate window. A window containing information about the knowledge discovery tool  100  or navigator tool  170  may be opened upon selection of the about button  1926 . This information may include version information, such as a revision number, intellectual property information, such as copyright, patent and/or licensing information, and the like. 
     The options button  1944  may launch the master options dialog. One embodiment of the master options dialog  2100  is shown in  FIG. 21 . In the embodiment of  FIG. 21 , the master preferences dialog  2100  includes a startup view preference  2110 , a navigation history preference  2120 , a related items limit preference  2130 , an animations preference  2140 , a reset button (not shown), an ok button  2150 , and a cancel button  2160 . 
     The startup view preference  2110  allows the user to select what they want to see upon starting the navigator tool  170 . In one embodiment, three options are provided: search, last item visited and home item. If the search option is selected, the navigator tools  170  opens with a search dialog, discussed below in more detail. If the last item visited option is selected, the navigator tool  170  opens with the active node  1838  from when the navigator was last closed. In one embodiment, all filter, confidence, and entity component  1832  association settings may also be preserved. Filter and confidence settings are described in more detail below. Finally, if the home item option is selected, the navigator tool  170  will open with the home item as the active node  1838 . Preferably, the home item startup option is the default option and the home view is set to a standard node. 
     The navigation history preference  2120  defines the number of navigation events stored for the navigation session. In one embodiment, the default value is set to 10. Alternatively, or in addition to, the navigation history preference  2120  may have a maximum value, for example, 30 events. Preferably, the navigation history preference  2120  is implemented as a drop down box. 
     The related items limit preference  2130  controls the number of records which can be returned to each entity panel  1932  in the navigator tool  170  from a query. In one embodiment, a default value is selected to optimally balance performance and quality of the results returned. 
     The animations preference  2140  may allow the user to enable or disable animation rendering effects in the user interface. Preferably, the animations preference  2140  is implemented as a checkbox and is selected by default. An ok button  2150  may be provided to accept the currently selected preferences, and a cancel button  2160  may be provided to close the dialog  2100  without changing preferences. 
     Referring again to  FIG. 19 , the search button  1928  may launch a search tool that allows the user to perform a keyword search of the knowledge model  140 . The search dialog may include the appropriate user interface tools to allow the user to specify a search term(s) for querying the knowledge model  140 . One embodiment of a search tool  2200  is shown in  FIG. 22 . To perform a search, a user may enter one or more keywords of interest in the search term field  2210 . The search will perform a literal search for the entered search terms. In one embodiment, a ‘*’ character acts as a wildcard identifier and denotes multiple characters. For example, a search for the keyword “ind*” may cause the knowledge model  140  to search for all terms starting with the text “ind.” The user may also be able to select the type of information they are looking for by checking an entity type from those listed in the menu  2220  of checkboxes below the search field  2210 . For example, one may restrict the results of a search to diseases, genes or literature by selecting the appropriate items in the menu. In one embodiment, the user may further refine a search target by selecting “Internal, External, or Both” under the literature entity. Preferably, the navigator tool  170  searches against all entities by default. 
     To begin a search, the user may click the find button  2212 . In response, the system  100  performs a free-text search against the information stored in the knowledge model  140 . When the search is complete, the results are shown in the Search Results field  2230 . In one embodiment, the search results include a description  2232  of the item and the entity table  2234  to which it belongs. The user may also be able to view more detailed information in the description field  2240  by selecting the item from the list. In one embodiment, the selection of an item is made via a single click on any of the search results. The results may be sorted by name or by type by clicking on the header of the appropriate fields  2232  and  2234 . The user may be able to view the source of a particular search result by clicking the View Web Page button  2250 . The Show button  2252  shows the selected item in the navigation window, making it the active node  1838 . Alternatively, or in addition to, the user may double-click a particular search result to make that item the active item  1838 . The Close button  2254  will close the search dialog box. 
     Referring again to  FIG. 19 , a bookmarks button  1930  may also be provided on the navigator toolbar  1510 . As described above, bookmarking an item allows the user to save links to previously viewed items to enable their quick retrieval later. Clicking the Bookmark button  1930  may cause a list of saved bookmarks to be displayed. An exemplary screen shot of the navigator tool  170  with a bookmark list  2310  is shown in  FIG. 23A . As shown, the bookmark list  2310  includes a list of bookmarks  2312 . Selection of a bookmark  2312  may cause the item that is bookmarked to become the active item  1838  of the navigator tool  170 . In one embodiment, bookmarks  2312  include a name. When a bookmark  2312  is created, the bookmark  2312  may have the same name as the item that is being bookmarked. Optionally, the user may rename the bookmark  2312 , for example, by clicking the right mouse button over the bookmark  2312  and selecting “Rename” from a popup menu and typing the new name. Bookmarks  2312  may also be deleted from the list, for example, by clicking the right mouse button over the bookmark and selecting “Delete” from a popup menu. 
     Optionally, bookmarks  2312  may be organized into folders much like computer files or internet bookmarks are managed. In one embodiment, the user may create a folder by clicking the right mouse button over the folder under which you want to create your new folder and selecting a “Create folder” option from a popup menu. Folders may also be renamed using a similar procedure as renaming bookmarks  2312  described above. A folder may also be deleted in a similar manner. Once a folder has been created, the user may organize bookmarks  2312  by dragging the bookmark  2312  (i.e., hold the left mouse button over the bookmark and move your mouse) to the folder. Folders may also be hierarchically arranged in a similar manner. In one embodiment, clicking a folder will alternatively show or hide the contents of that folder. 
     Optionally, bookmarks  2312  may be shared among users. In one embodiment, the system  100  may notify users of a common interest in particular item if one or more colleagues have the same bookmark  2312  by creating a special bookmark that is added to each users list  2310 . Selection of this special bookmark may open a shared bookmarks tool. One embodiment of a shared bookmarks tool  2320  is shown in  FIG. 23B . The shared bookmark tool includes information about the subject item  2322 , such as an item name, as well as information about each user sharing the interest. In one embodiment, each users&#39; first name  2324 , last name  2326 , and email address  2326  are displayed. It should be apparent to one of ordinary skill in the art that other information may be displayed. Optionally, the user may elect not to share a bookmark with colleagues. Alternatively, or in addition to, users may be notified of common bookmarks by other methods, such as via email, instant messages, pop-up windows, and the like. 
     Referring again to  FIG. 19 , a wizards button  1930  may be provided to allow the user to launch a wizard service. In one embodiment, the wizard service may guide the user through a series of screens to formulate a search. For example, the wizard service may assist with the process of identifying existing assets that have indication in a specified area. An exemplary area may be a particular disease. Exemplary assets may be compounds into which research efforts have been invested. For a knowledge model  140  for pharmaceutical research, the wizard may take user selected diseases and targets as inputs, allow the user to also specify genes, proteins, or pathways, and then and return a list of possibly relevant projects, literature and compounds, as related by the knowledge model  140 . 
     Exemplary screen shots of a wizard service are shown in  FIGS. 24A-L . In one embodiment, there are three stages to the workflow of the wizard service. As shown in  FIG. 24A , the user may initially choose to create a new search  2402  or load a previously saved search  2404 . Saved searches may be retrieved via a drop-down list  2406 . Next, the user may define the scope of the analysis. For example, diseases experts and target class representatives identify their initial area of interest such as a disease  2408  or a target  2410 , or both  2412 , through the use of the wizard, as shown in  FIG. 24B . Depending on their selection, the wizard service will guide the user through a series of screens to further define the scope of the search. 
     Next, matching terms are searched and allow user to select one or more matching terms to augment or refine search parameters. An exemplary process for determining additional keywords for diseases is shown in  FIGS. 24C-D . Based on the input keyword  2414 , the wizard service may assist the user to enhance the list of terms  2416  by providing them with a list of diseases including the keyword  2414 , as shown in  FIG. 24C . Additionally, the user may choose  2418  to include known related diseases, such as parent and/or child diseases, as shown in  FIG. 24D . If the user so chooses  2418 , a list of known related diseases  2420  may be displayed. The may choose to include any or all of the related diseases in the search. Similarly, the user may select targets by entering a target keyword  2422  and selecting targets that include the keyword  2424 , as shown in  FIG. 24E . Once the user has defined the diseases and/or targets to include in the search, the user may be be provided with a list of current diseases  2426  and/or targets  2428  and prompted to validate the selections, as shown in  FIG. 24F . At this point, the user may edit the search parameters associated with each of the diseases  2426  and/or targets  2428 . 
     Next, the user may choose to augment the search to include additional keywords from topics such as genes  2430 , proteins  2432 , and pathways  2434 , as shown in  FIG. 24G . In each case, the user may be presented with a list of additional keywords and have the ability to select any keywords from the list to include them in the search. As shown in  FIG. 24H , the user may be presented with a list  2436  of genes related to the selected diseases and/or targets. The user may then select any of the genes to add them in the search. Optionally, the user may also provide keywords  2440  to search for additional genes including the keyword  2440 . Genes including the keyword  2440  may be displayed in the corresponding field  2438 , and the user may select any gene from the list to include it in the search. Additionally, or alternatively, the user may also be able to directly add a known gene to the scope of a search by manually entering the gene into the appropriate field  2442 . Similar processes may be included for adding protein and pathway related keywords to the search, as shown in  FIGS. 24I and 24J . 
     The result of this first stage is a collection of keywords that are related by the knowledge model  140 . At this point, the user may be prompted to validate the scope of the search, as shown in  FIG. 24K . A list of all keywords  2444  may be displayed. In one embodiment, the user may then choose to go back to any of the previous steps and further refine the scope of the search. The user also have the option to save  2446  the query at this point. In one embodiment, the user may save the query by entering a query name. 
     Once all the terms have been finalized, the wizard submits the query and collates the results. In one embodiment, these keywords may be searched against project and literature databases, for example, by submitting search strings to the database search indices to find, for example, projects and literature that match the list of relevant terms. The wizard service may return a set of projects/literature that match the set of query terms. Preferably, the query terms may be ranked and organized by the number of relevant search terms that were found in each search result. Thus, a results list of pointers to projects and literature that mention the keyword combinations within the analysis scope may be created. 
     Finally, the user reviews the results identified to review potentially applicable projects and literature and compounds, as shown in  FIG. 24L . In one embodiment, selecting an item on the results lists  2448  and  2450  causes that item to become the active node  1838 . When an item of the results list is selected, that item takes centrals focus in navigator tool  170 , allowing the user to rapidly build an understanding of the item selected and to explore the knowledge model  140  around the project/asset to add context and explore related literature and topics. 
     Referring again to  FIG. 19 , a monitored items button  1934  may be provided to launch a monitored items dialog that allows the user to select to be notified when new relationships or literature are discovered for a particular item. An exemplary monitored items dialog  2500  is shown in  FIG. 25 . The monitored items dialog  2500  includes a last publication date  2510  which represents the most recent date on which new information was integrated into the knowledge model  140 . The dialog also includes a list  2512  of all monitored items that have changed since the items associated monitoring date and the last publication date  2510 . 
     Referring again to  FIG. 19 , a filters button  1936  may be provided to launch a filters dialog that allow the user to establish filter settings that filter the related items  1940  being displayed in an entity component  1932 . In general, filters are a mechanism for focusing the results displayed in the navigator tool  170 . Preferably, the filters are implemented as client-side applications. It should be apparent to one of ordinary skill in the art that the number of filters available for an entity component may vary based on the data stored in the associated knowledge model  140  table. Preferably, several types of filters are accessible directly from the Navigator panels. The entity component  1832  should display a filter icon  1844  if one or more filters exist for that pane. Clicking on the filter icon may also launch the filters dialog. 
     An exemplary filters dialog  2600  is shown in  FIGS. 26A-E . The filters dialog  2600  may include several tabbed filter options pages in which the user may specify various filtering options, such as general filter options, entity filtering options, journal filtering options, publication filtering options, and the like. In one embodiment, general filtering options include filter persistence  2602  and internal/external filtering  2604 . If the user selects persistent filtering  2602 , the navigator tool  170  will filter the results of each navigation event. Otherwise, the navigator tool will only filter the current navigation event. Toggling the internal/external filtering option  2604  allows the user to limit results to data source that are internal or external to their enterprise. 
       FIG. 26B  shows an exemplary screen shot of a entity filter options page. Entity filtering allows the user to specify parameters to filter the display to show only those related items  1840  that relate to specific entities. Exemplary entity filter entities for a pharmaceutical research navigation tool include organisms and phenotypes. In one embodiment, the user may specify a list of phenotypes  2610  and/or organisms  2612  to display. The user may edit the list of displayable organisms by selecting the edit list button  2614 , which may launch a dialog  2620  as shown in  FIG. 26C . The user may then view a list of available organisms  2622  by entering a keyword or selecting the appropriate first letter of the organism name from the alpha-bar  2626 . The user may then select organisms to add or remove from the list of displayable organisms  2628 . A similar dialog may be used to edit the phenotype list. 
     The user may also be able to filter displayed literature items to those items found in particular journals. An exemplary screen shot of a journal fitler options page is shown in  FIG. 26D . The user may specify a list of displayable journals  2630  in a similar manner to the organism and phenotype lists described above. Additionally, the user may specify a threshold journal impact level via the corresponding controls  2632 . In one embodiment, the journal impact level corresponds to an ISI journal impact ranking. Finally, the user may also be able to filter items based on their publication date, as shown in  FIG. 26E . In one embodiment, the user may limit the results to items published within a set amount of time  2640 , or to those items published before a certain date  2642 . 
     Referring again to  FIG. 19 , an internal/external filter button  1938  may be provided to allow the user to select related items  1940  based on the source from which they were obtained, as describe above. A confidence box  1940  may also be provided to allow the user to filter the items  1940  displayed in all entity components  1930  based on confidence values. These filters are referred to as confidence filters. In one embodiment, the confidence box  1940  is implemented a button associated with each confidence value may be provided to allow the user to display/hide links of the corresponding confidence value. Alternatively, the confidence button  1940  may be implemented as a list of confidence values wherein the navigator tool only displays those items  1940  meeting the selected threshold confidence value. In yet another embodiment, the confidence button  1940  may be implemented as a text box that establishes a threshold confidence value and only those related items  1940  meeting the threshold value may be displayed. The threshold confidence value may be indicative of the relationship type, as described above. For example, a threshold value of one may correspond to a direct relationship. 
     A context drop down list  1942  may be included to provide the user with a list of previously saved, or system provided, stored sets of context. A context represents a set of navigator tool settings. In one embodiment, a context includes filter settings, confidence filter settings, and panel layouts. Alternatively, or in addition to, the context drop down list  1942  may also provide access to personal and group default preferences sets associated with login information. Upon selection of a context set, the navigator tool  170  will update the current display to reflect the newly selected context. Alternate context sets containing various sets of information should be readily apparent to one of ordinary skill in the art. For example, master context information may also be stored in a context set. The context drop down list  1942  may display a list of stored preference sets by name. In one embodiment, a user may save a new context by selecting a “save new” option from the context drop-down list  1942 . 
     It is therefore intended that the foregoing detailed description be regarded as illustrative rather than limiting, and that it be understood that it is the following claims, including all equivalents, that are intended to define the spirit and scope of this invention.