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WP 3: Enhancing eLearning with semantic knowledge M25-M30 Activities

WP 3: Enhancing eLearning with semantic knowledge M25-M30 Activities. Kiril Simov Review Meeting, Luxembourg, 29 August 2008. Plan of the Talk. Preliminaries – the results of the second year Incorporation of feedback on ontology New concept added to the ontology Lexicons extensions

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WP 3: Enhancing eLearning with semantic knowledge M25-M30 Activities

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  1. WP 3: Enhancing eLearning with semantic knowledgeM25-M30 Activities Kiril Simov Review Meeting, Luxembourg, 29 August 2008

  2. Plan of the Talk • Preliminaries – the results of the second year • Incorporation of feedback on ontology • New concept added to the ontology • Lexicons extensions • New annotation grammar and re-annotation of Los • Addition of Maltese lexicon • Improvement of integration with ILIAS • New functionalities • Improved performance • New user interface

  3. WP3: Goals Creation of ontology and ontology system to support: • Classification of learning objects Annotation of LOs with concepts – ontology search • Multilingual search for learning objects Media between the different languages

  4. Where We Stand: Second Year • Target domain: Computer Science for non-computer scientists • First version of the ontology • Evaluation of the ontology – consistency and coverage • Ontology-to-text relation: annotation of learning objects • User validation

  5. Revision of the Ontology • We have received suggestions for new concepts from partners on the basis of: • the annotation of LOs • the preparation of validation scenarios • comparison to online sources (Wikipedia) • The new concepts were added to the ontology • The upper part was additionally simplified • The result ontology includes 1002 domain concepts, 274 upper concepts

  6. Extension of Lexicons • The lexicons for all languages were extended to cover • the new domain concepts; • the concepts from the upper part • the properties • Definition in other languages than English were added

  7. Lexicon for Maltese • The problems with implementation of the system functionalities for Maltese were based on: • missing language tools for Maltese at the beginning of the project, and • not enough learning materials in Maltese. • The work was concentrated on the lexicon • Maltese is included as a query language

  8. Re-annotation of Learning Objects • Grammars were extended on the basis of the new terms in the lexicons • The main problem was the interaction between the old grammar rules and the new ones: "Microsoft Word document"  "Microsoft Word“ • The grammars were divided in two parts • Different application rules • Statistical disambiguation

  9. Evaluation of Ontology • Ontology covering of the domain • The new concepts added on the basis of the annotation of the learning objects and the comparison with online resources ensure better coverage of the domain • Restructuring of the ontology • Deleting unary branches from the OntoWordNet • Grouping of related concepts

  10. Semantic Search vs. Text Search • During the second year we performed comparison between the two kinds of search • The results were very attractive, but not very fair with respect to advanced text search • During 25-30 M period we studied different kinds of textual search, but there were no resources for their implementation

  11. Ontology as Interlingua • Existence of ontologies • Ontologies created for other purposes, but reused in eLearning • Addition of a new language • Mapping to the ontology ensures correspondences to all other languages • Reasoning • Ontology supports reasoning for better search (especially for cross-lingual search)

  12. New WP3 Functionality • On the basis of the users' feedback several WP3 functionalities were added or improved. The most important are: • AND/OR search • snippet extraction • relevance score • concept-LO tables

  13. AND/OR Search • Applied to both kind of search: manually entered search terms; and for selected concepts • No special syntax is implemented • The AND/OR options have effect on two elements of the search procedure: • Combination of multi-word terms • Combination of found concepts

  14. Combination of Multi-Word Terms • In case the OR option is selected, combinations for multi-word terms are created: for query terms “computer” and “screen” additional terms are created: “computer screen”, “computerscreen”, “somputer-screen” • In case the AND option no extra combinations of words are created

  15. Combination of Found Concepts • In OR-search, a document is retrieved if it contains any relevant concept: query concepts or their sub-concepts • In AND-search, however, it is not possible to take the conjunctive of all those concepts. Certain concepts should be treated as alternatives – for examples, the sub-concepts of a concept are integrated in the query as a disjunction

  16. Snippet Extraction • A Google-like text snippet for each retrieved document, which shows the context of the word or concept in the document • In case of semantic search, it is selected around occurrences of the matching concepts • A highlighted word can be different from the search term

  17. Relevance Score and Ranking • Relevance score is an aggregation of two scores: • the number of different ''main search concepts'' that match the document • the occurrence frequency of the matched concepts, including the inferred concepts (normalized for document length) • Document ranking is based on “expected concept-token-ratio”

  18. Tool for Concept-LO Tables • A tool that creates tables for manual inspection of the concept-LO relations • The tool creates three different representations of the concept-document relations: • Concept to Document • Document to Concept • Document  Concept  All superconcepts

  19. Mind Map as Visualization Tool • We have studied some implementation of Mind Map and concluded: • Very attractive visualization tool for different kinds of resources • No implementation of Mind Map is ready to be used directly in LT4eL • Not possible to do adapt and to evaluate them during the last 6 months • Future work within LTfLL project

  20. Conclusion • The work during the last 6 months was guided by the evaluation of the system • We have extended the ontology, lexicons and annotation grammars • Maltese lexicon was added • We have re-annotated the LOs • New functionalities were implemented and integrated within ILIAS

  21. Plans for Future Work • Other applications of domain ontology within eLearning environment • Further development of ontology-to-text relation • Development of better annotation grammar • Design and implementation of better visualization tool • Improvement on the search

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