RT Journal Article
T1 Implementing WordNet Measures of Lexical Semantic Similarity in a Fuzzy Logic Programming System
A1 Pascual, Julián_Iranzo
A1 Sáenz Pérez, Fernando
AB 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.
PB Cambridge University Press
SN 1471-0684
SN 1475-3081
YR 2021
FD 2021-03
LK https://hdl.handle.net/20.500.14352/114018
UL https://hdl.handle.net/20.500.14352/114018
LA eng
NO 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
NO 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.
NO Ministerio de Ciencia e Innovación (España)
NO Ministerio de Economía, Comercio y Empresa (España)
NO Comunidad de Madrid
NO European Union
DS Docta Complutense
RD 27 dic 2025