Implementing WordNet Measures of Lexical Semantic Similarity in a Fuzzy Logic Programming System

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...

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Bibliographic Details
Published in:Theory and practice of logic programming 2021-03, Vol.21 (2), p.264-282
Main Authors: JULIÁN-IRANZO, PASCUAL, SÁENZ-PÉREZ, FERNANDO
Format: Article
Language:English
Subjects:
Algorithms
Fuzzy logic
Logic programming
Mathematical analysis
Natural language processing
Programming languages
Similarity
Words (language)
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Summary: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 (NLP) applications.
ISSN:1471-0684
1475-3081
DOI:10.1017/S1471068421000028