Implementing WordNet Measures of Lexical Semantic Similarity in a Fuzzy Logic Programming System
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2021
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Cambridge University Press
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JULIÁN-IRANZO P, SÁENZ-PÉREZ F. Implementing WordNet Measures of Lexical Semantic Similarity in a Fuzzy Logic Programming System. Theory and Practice of Logic Programming. 2021;21(2):264-282. doi:10.1017/S1471068421000028
Abstract
This paper introduces techniques to integrate WordNet into a Fuzzy Logic Programming system. Since WordNet relates words but does not give graded information on the relation between them, we have implemented standard similarity measures and new directives allowing the proximity equations linking two words to be generated with an approximation degree. Proximity equations are the key syntactic structures which, in addition to a weak unification algorithm, make a flexible query-answering process possible in this kind of programming language. This addition widens the scope of Fuzzy Logic Programming, allowing certain forms of lexical reasoning, and reinforcing Natural Language Processing applications.
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Work is partially funded by the State Research Agency (AEI) of the Spanish Ministry of Science and Innovation under grant PID2019-104735RB-C42 (SAFER), by the Spanish Ministry of Economy and Competitiveness, under the grants TIN2016-76843-C4-2-R (MERINET), TIN2017-86217-R (CAVI-ART-2), and by the Comunidad de Madrid, under the grant S2018/TCS-4339 (BLOQUES-CM), co-funded by EIE Funds of the European Union.