Publication | Closed Access
Semantic relationship discovery with wikipedia structure
14
Citations
7
References
2011
Year
EngineeringKnowledge ExtractionSemantic Relationship DiscoveryNovel Method RcrankSemantic WebSemanticsCorpus LinguisticsText MiningNatural Language ProcessingSocial Semantic WebInformation RetrievalData ScienceConcept RecommendationLanguage StudiesKnowledge DiscoverySemantic NetworkRelationship ExtractionSocial CollaborationSemantic Social NetworkLinguisticsSemantic Similarity
Thanks to the idea of social collaboration, Wikipedia has accumulated vast amount of semi-structured knowledge in which the link structure reflects human's cognition on semantic relationship to some extent. In this paper, we proposed a novel method RCRank to jointly compute concept-concept relatedness and concept-category relatedness base on the assumption that information carried in concept-concept links and concept-category links can mutually reinforce each other. Different from previous work, RCRank can not only find semantically related concepts but also interpret their relations by categories. Experimental results on concept recommendation and relation interpretation show that our method substantially outperforms classical methods.
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