Selection and information: a class-based approach to lexical relationships
Selection and information: a class-based approach to lexical relationships
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contextual correlates of synonymy
Communications of the ACM
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ACM Transactions on Information Systems (TOIS)
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Verbs semantics and lexical selection
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Algorithmic detection of semantic similarity
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OTM '09 Proceedings of the Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: ADI, CAMS, EI2N, ISDE, IWSSA, MONET, OnToContent, ODIS, ORM, OTM Academy, SWWS, SEMELS, Beyond SAWSDL, and COMBEK 2009
Evolving semantics for agent-based collaborative search
AAMAS'11 Proceedings of the 10th international conference on Advanced Agent Technology
Journal of Biomedical Informatics
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Defining a suitable semantic similarity between concept pairs of a subsumption hierarchy is becoming a generic problem for many applications in knowledge engineering exploiting ontologies. In this paper, we define a generic framework which can guide the proposition of new measures by making explicit the information on the ontology which has not been integrated into existing definitions yet. Moreover, this framework allows us to rewrite numerous measures, originally proposed in various contexts, which are in fact closely related to each other. From this observation, we show some metrical and ordinal properties. Experimental comparisons on Word-Net and on collections of human judgments complete the theoretical results and confirm the relevance of our propositions.