Publication | Closed Access
Semantic cores for representing documents in IR
54
Citations
16
References
2005
Year
Unknown Venue
Ontology MatchingEngineeringSemantic SearchSemantic TechnologySemanticsSemantic WebCorpus LinguisticsSocial SciencesText MiningNatural Language ProcessingInformation RetrievalSemantic ApproachData IntegrationSemantic Knowledge ManagementOntology LearningSemantic CoresKnowledge RetrievalKnowledge DiscoveryComputer ScienceSemantic ComputingIntelligent IndexingSemantic RetrievalLinguisticsSemantic Similarity
This paper deals with the use of ontologies for Information Retrieval. Roughly, the proposed approach consists in identifying important concepts in documents using two criterions, co-occurrence and semantic relatedness and then disambiguating them via an external general purpose ontology, namely WordNet. Matching the ontology and a document results in a set of scored concept-senses (nodes) with weighted links. This representation, called semantic core of a document best reveals the semantic content of the document. We regard our approach, of which the first evaluation results are encouraging, as a short but strong step toward the long term goal of Intelligent Indexing and Semantic Retrieval.
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