Source: http://www.google.de/patents/US8037083
Timestamp: 2013-06-19 20:09:56
Document Index: 233686600

Matched Legal Cases: ['Application No. 06023169', 'Application No. 06023169', 'Application No. 06023169', 'Application No. 06023169', 'Application No. 06023169', 'Application No. 06023169', 'Application No. 06023169']

Patent US8037083 - Lossless format-dependent analysis and modification of multi-document e ... - Google PatenteSuche Bilder Maps Play YouTube News Gmail Drive Mehr » Erweiterte Patentsuche | Webprotokoll | Anmelden Erweiterte Patentsuche PatenteContent stored in a plurality of electronic files that belong to a course of learning resources is read. An object-oriented representation of structures of the content is generated, where the representation includes objects that represent portions of the content, and a semantic content model of the content...http://www.google.de/patents/US8037083?utm_source=gb-gplus-sharePatent US8037083 - Lossless format-dependent analysis and modification of multi-document e-learning resources Ver�ffentlichungsnummerUS8037083 B2PublikationstypErteilung Anmeldenummer11/287,628 Ver�ffentlichungsdatum11. Okt. 2011Eingetragen28. Nov. 2005 Priorit�tsdatum28. Nov. 2005Auch ver�ffentlicht unterDE602006011565D1, EP1791067A1, EP1791067B1, US20070124322 Ver�ffentlichungsnummer11287628, 287628, US 8037083 B2, US 8037083B2, US-B2-8037083, US8037083 B2, US8037083B2 ErfinderTomas Hildebrandt, Marek MeyerUrspr�nglich Bevollm�chtigterSap AgPatentzitate (24), Nichtpatentzitate (21), Referenziert von (2), Klassifizierungen (9) Externe Links: USPTO, USPTO-Zuordnung, EspacenetLossless format-dependent analysis and modification of multi-document e-learning resourcesUS 8037083 B2 Zusammenfassung Content stored in a plurality of electronic files that belong to a course of learning resources is read. An object-oriented representation of structures of the content is generated, where the representation includes objects that represent portions of the content, and a semantic content model of the content is generated based on the object-oriented representation of the content. Instructions to modify the content are received and the object-oriented representation of the structures of the content is modified in response to the instructions from the user. In response to the modified object-oriented representation of structures of the content the content is modified.
TECHNICAL FIELD This description relates to managing electronic content and, in particular, to lossless format-dependent analysis and modification of multi-document e-learning resources.
BACKGROUND On-line learning tools, courses, and methods have been developed from computer-based delivery (CBT) systems, in which learning resources were depicted as being as atoms or Lego� blocks of content that could be put together or organized to create semantic content. Standards bodies have refined the concept of learning resources into a rigorous form and have provided specifications on how to sequence and organize these bits of content into courses and how to package them for delivery as though they were books, training manuals, or other sources of instructional content.
Electronic instructional content (or �e-learning�) for educational, training, infomercial, or entertainment purposes can be delivered to a user through many media (e.g., the Internet, television, playable storage media, such as videotapes, DVDs, CDs, intelligent tutoring systems, and CBT). The instructional content can be delivered to a user in many different forms (e.g., tests, training programs, and interactive media) and is generally referred to herein as a �course.� In general, e-learning courses are suites of electronic learning resources (i.e., pieces of data that are used in an e-learning course) and can be composed of modules and lessons, supported with quizzes, tests and discussions, and can be integrated into educational institution's student information system, into a business's employee training system, or any other system in which learning occurs. The learning resources of an e-learning course can be composed of numerous files of many different formats (e.g., text files, PDF files, multimedia files, including jpeg, mpeg, wave, and MP3 files, HTML, and XML files). The number and complexity of the different learning resources in a course can be high and the relations and interfaces between the different learning resources also can be complex.
SUMMARY In a first general aspect, a method includes reading content stored in a plurality of electronic files, where the files belong to a course of learning resources. An object-oriented representation of structures of the content is generated, where the representation includes objects that represent portions of the content, and a semantic content model of the content is generated based on the object-oriented representation of the content. Instructions to modify the content are received and the object-oriented representation of the structures of the content is modified in response to the instructions from the user. In response to the modified object-oriented representation of structures of the content the content is modified.
BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a schematic block diagram of a framework for modifying an e-learning course.
DETAILED DESCRIPTION As described herein, a common, format-independent representation of the content of all of the multiple learning resources of an e-learning course is created from the actual learning resources themselves. �Content� as used herein refers to both the data and the semantic content in the learning resources. The learning resources can be files or �documents� of many different types, including, for example, text, graphics, photos, animation, simulation, audio, and video, and many be stored in a variety of different formats (e.g., PDF, MPG, JPG, AVI, CSS, DOC, GIF, HTML, MIDI, MP3, MOV/QT, PNC; RAR, TIFF, TXT, WAV, BIN, CSS, PPT, XLS, and ZIP). Documents can be sub-divided into modules, although a document itself can be a module. A course consists of a collection of different learning resources. The format-independent representation of the content is created in a manner such that no information is lost when creating the representation, and the representation is then used to analyze and modify the course, such that the user is not burdened by the format-dependency of the individual learning resources.
The representation consists of three layers: the physical files of the learning resources, which are stored in a storage medium; a tree-like object-oriented model representing the structures of the learning resources (e.g., a tree of Java objects for the document model); and a semantic model that contains an outline of the content including semantic relations and decoration (e.g., a Resource Description Framework (�RDF�) model for the semantic model). The models are sequentially built in a bottom-up approach. Thus, the object model is built by reading learning resource documents or modules from a storage device and creating an object tree from the content in the documents or modules. The semantic model is built based on the object model and provides information about the semantic content of the course to a user. The user then analyzes the semantic content model and makes modifications that are implemented as modifications within the object model. The modifications then are propagated to the learning resource modules stored on the storage device without losing relevant information.
FIG. 1 is a block diagram of a framework 100 for organizing, analyzing and re-authoring an e-learning course composed of learning resources. The framework 100 is organized in three main blocks: a content model block 102, a semantic enrichment block 104, and a Modification Transaction Engine (�MTE�) 106. An application layer 108 through which a user accesses the learning resources and representations of the learning resources communicates with the three blocks 102, 104 and 106 to allow the user to perform different tasks. The content model block 102 is used for analysis of the content of the course. The semantic enrichment block 104 is used for controlling the level of detail in the content model. The MTE 106 is used to modify the content in the course.
The content model block is divided into three layers: a physical files (�PF�) layer 110, a document object model layer (�DOM�) 112, and semantic content model layer (�SCM�) 114, which are stacked one on top of the other within the framework 100. The physical files layer 110 is responsible for handling access to the physical files and directories of the learning resources (e.g., the HTML, PDF, TXT, MPG; JPG, etc. files that contain the content of the course). This includes access to the file system, working with the directory structure, as well as reading and writing files. Format plug-ins, as described below, may add support for modifying files on disk to the PF layer 110.
The DOM 112 is an object-oriented model that contains an outline (e.g., an object tree) that is created based on the structure of the documents in the physical files layer 110. After the object tree is created, the tree is transferred to the semantic content model 114, in which entities within the semantic model are marked so that they can be uniquely mapped to the entities of the DOM 112. Thus, the SCM 114 is a more abstract representation of the course content, containing only selected parts of the DOM structure but enriched with explicit semantic and didactic information about the content. The SCM 114 is complemented by a content ontology (�CO�) 116 that provides conceptual knowledge about the used types of entities and relations.
The semantic enrichment block 104 contains one or more semantic enrichment components (�SEC�) 118, which analyze the semantic content model 114 in order to make implicit semantics explicit to the semantic content model 114. An SEC 118 may also use and add external knowledge to fulfill this task. Thus, semantic relations can be added to the semantic content model 114 both during the conversion and afterwards as a result of a more intensive content analysis. The semantic content model 114 is then ready to be used for an analysis of the content.
Referring to FIG. 2, the DOM can be a tree-like object-oriented representation 200 of the content in the learning resources of a course. The learning resources can be stored in the form of generic documents, and for each document that belongs to the content, a new partial DOM (�pDOM�) can be created. These pDOMs are then joined to one single DOM by adding references from a sub-document's pDOMs to a parent document's pDOM. That is, the content DOM is a tree which consists of sub trees for the particular documents. Thus, a pDOM 202 that relates to an image of a person can be a sub-document of a pDOM 204 that relates to video footage of the person, which, in turn, can be a sub-document of a pDOM 206 that relates to a biographical story about the person. Additionally, a document containing textual information about the person can be a pDOM 208 of the pDOM 206. Together, pDOM's 202-208 can be joined in a tree 200 as a single DOM that relates to a multi-media biography about the person.
In one example, documents formatted in IMS Content Packaging (IMS-CP), HTML, and JPEG can store the content of learning resources of a course. In the IMS-CP protocol, a Content Package is a compressed file (usually a zip file) that contains the learning object, its metadata record, and a manifest describing the contents of the package. The document object model 200 for IMS-CP documents can consist of Java classes and objects, in which the generic DOM 200 is built out of a set of pDOM java classes that represent standard types of document fragments and structural elements such as �TextFragment,� �StructuralElement,� �Title,� or �Image.� These java classes can be extended to include additional classes. For example, for representing IMS-CP documents, a class �OrganizationItem� can be defined and used to refer to documents relating to organizational content of a course, thus extending the �StructuralElement� class. Instances of the OrganizationItem class can be instantiated at run-time to represent structural items of the content package's manifest. The manifest itself can be an XML file, which can be read into memory by a standard XML-DOM library. Each instance of the class �OrganizationItem� therefore contains a reference to the corresponding standard DOM object. The data are stored primarily in the XML-DOM, and the CP objects provide only a view of the XML-DOM to simplify the access to the data. CP objects contain mainly getter/setter methods as well as special methods to access subordinated or referencing objects. In addition, the CP objects can work as a cache to accelerate access to the data. For example, an object �CPOrganization� can be assigned to an �OrganizationItem� element of the XML-DOM. The CPOrganization object permits the reading and writing of the �StructuralElement� and �Title,� attributes, produced by requests from a list of the subordinate �Items� objects and can insert new items.
Similarly, for HTML document, generic content classes can be extended to suit the particularities of HTML. For example, there may be an �HTMLTitle� class which extends the �TextFragment� element and represents the <title>-element of an HTML document. In the background a standard HTML-DOM is used for reading and writing the document.
As shown in FIG. 3, a base SCM graph 300 can be automatically constructed from the DOM and contains nodes 302, 304, 306, and 308 that reference each document object in the DOM as well as a relation of the type �part of� to the root node 302 of the graph, which provides an enclosing container for the whole content. A �before� and �after� relation is inserted between content nodes to refer to the sequential information of the content. For example, node 304 contains a �before� relation to node 306, and node 306 contains an �after� relation to the node 304 to indicate that semantic content identified in the node 304 comes sequentially before the semantic content identified by node 306 in the course described by the graph 300. Each node is marked with a unique identifier that references the underlying document object in the DOM. RDF libraries often contain their own query language such as RQL, RDQL or SeRQL, which are suited for analysis of the SCM.
For example, when a user wants to modify a course by translating its content into a different language, the user may want to know the language of text fragments and also have quotations marked, so that direct quotations will remain in their original language in spite of the translation modification. Two separate SECs can be designed for performing the tasks of identifying and marking the language of text fragments and for locating quotations in the text, so that they can be re-used independent from each other for other applications. The first SEC is responsible for determining and marking the language of text fragments. It requests all text fragments from the SCM and, based on comparisons to dictionaries of different languages it decides which language each fragment most probably belongs to. The text fragment entity is marked by adding a language property to the text fragment in the SCM 114. The second SEC identifies quotations inside text fragments. This component requests all text fragments and analyzes them. Multiple indicators can be used for recognizing quotations, for example, the explicit usage of markup such as the <q> and <blockquote> tags in HTML can be used. Another indicator is the use of quotation marks, although this one is less reliable. To all identified text entities in the SCM 114 a type �Quotation� can be added in the SCM.
Several examples of valid commands could be: (CMD_DELETE, 376), which would delete the node with identified as (RDF-)ID 376; (CMD_MOVE, 13, 412), which would relocate the node 13 to a location below node 412; (CMD_REPLACE_TEXT, 14, �new text�), which would change the text of node 14 with the string, �new text�; and (CMD_REPLACE_Image, 32, �c:/images/new_image.jpg�), which would replace the image node 14 by a new image that has to be copied from the file identified as �c:/images/new_image.jpg.� Thus, the MTE 106 is responsible for mapping the given node identifiers in the SCM 114 to the corresponding objects in the DOM 112, mapping the given command identifiers to object methods, converting the arguments (content nodes and simple values) to match the methods' signatures, and calling the object methods that perform a transaction execution.
The Modification Transaction Engine (MTE) 106 can be implemented as a Java component that accepts modification commands as method calls. This method may have a signature such as modificationCommand(List command), where the command list contains the values of a command tuple. Command identifiers are expressed constants, entity identifiers as URI strings. The MTE has access to a hash table where the Java object in the DOM corresponding to each entity in the SCM is stored. When the MTE is given a command it first resolves the entity identifiers into Java object references. Then it identifies the object whose method has to be called to execute the command. For example, the command (CMD_REPLACE_TEXT, 14, �new text�), which issues an instruction to replace the text in node 14 with the text �new text,� would be transformed into (CMD_REPLACE_TEXT, <java_object_x>, �new text�) first. Because the MTE knows the command template for �CMD_REPLACE_TEXT�, it identifies <java_object_x> as the object in charge and the given string �new text� as single argument for the object's method replaceText. This method replaceText is finally called with the call �java_object_x.replaceText (�new text�).�
Referring to FIG. 5, the framework 100 can be used in a process 500 for modifying the content of an e-learning course. In the process, an object-oriented representation of structures of the content in an e-learning course are generated (step 502), and a semantic content model of the content is generated based on the object�oriented representation (step 504). Thereafter, the semantic content model is analyzed (step 506) and instructions are received from a user to modify the content (step 508). The object-oriented representation of the structures of the content is modified in response to the instructions from the user (step 510), the content in the e-learning resources is modified in response to the modified object-oriented representation of structures of the content (step 512).
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Dez. 2009International Business Machines CorporationFlexible configuration item reconciliation based on data source prioritization and persistent ownership tracking* Vom Pr�fer zitiertKlassifizierungen US-Klassifikation707/756, 434/118Internationale KlassifikationG06F7/00 UnternehmensklassifikationG06F17/30056, G06F17/3002, G06F17/30038 Europ�ische KlassifikationG06F17/30E2M, G06F17/30E1, G06F17/30E4P1DrehenOriginalbildGoogle-Startseite - Sitemap - USPTO-Bulk-Downloads - Datenschutzerkl�rung - Nutzungsbedingungen - �ber Google Patente - Feedback gebenDaten bereitgestellt von IFI CLAIMS Patent Services.© 2012 Google