Taking into account communities of practice’s specific vocabularies in information sharing
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The document discusses the challenges of information sharing within communities of practice due to specific vocabularies and language variability. It presents a methodology for creating a formal ontology from identified communities and using it to facilitate semantic indexing and searching. This methodology involves multiple steps, including text analysis, lexicon development, ontology creation, and semantic searching, ultimately enabling automatic document indexing and improved retrieval of relevant information regardless of language differences.
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Taking into account communities of practice’s specific vocabularies in information sharing
- 1. Taking into account communities of practice ’s specific vocabularies in information sharing Luc Damas Cécile Million-Rousseau
- 2. Context Research fields Ontologies Terminologies Documents management Communities of Practice Ontologos corp : Knowledge management solutions Condillac Research Group : Knowledge management research
- 3. Keyword search VS Concept search Information sharing between: Langs Communities of practice Question : How can we get information about a topic when specific languages are used? Example: Searching information about « monkey » Can’t find informations about « primate » Specific vocabulary Can’t find informations about « singe » (french word for monkey) Language variability
- 4. Our solution Having a conceptual structure: formal ontology Having multiple communities: speciality languages Regrouping words: terminologies Animal Mammal … … … … … … … Primate singe French monkey English hominides … Scientist mamifère French
- 5. Methodology 1. text to lexicons First step in our methodology Prerequisites Communities of practice are identified Domain experts select a set of representative documents Task Linguistic tool automatialy extract candidate terms Co-occurrence Linguistic rules
- 6. Methodology 2. lexicon to ontology Domain expert and cognitive engineer work together Task Structuration of lexicon Use of semantic network Validation by users The most difficult task Ontology contains consensual terms These terms are often not used
- 7. Methodology 2. ontology to terminologies Ontology is submitted to users Users gives uses their own language to designate concepts Difficult task: need users, need time
- 8. Methodology 3. semantic indexing From now, everything is automatic! A document is indexed by: Searching all terminologies terms in the documents Adding in a semantic marker all the designated concepts Result Documents have semantic marker that are containing concept, independently from languages
- 9. Methodology 4. semantic searching Automatic too! With options! Searching an expression: Find the expression in terminologies Keep associated concepts Searching concepts in semantic markers Returning associated documents, with pertinence Options: Searching more general or more specific concepts Selecting langs …
- 10. Validation Our methodology is used in big companies Questions? [email_address] Thanks