WordNet lexical-database groups English words into sets of synonyms called "synsets." Synsets are utilized for several applications in the field of text-mining. However, they were also open to criticism because although, in reality, not all the members of a synset represent the meaning of that synset with the same degree, in practice, they are considered as members of the synset, identically. Thus, the fuzzy version of synsets, called fuzzy-synsets (or fuzzy word-sense classes) were proposed and studied. In this study, we discuss why (type-1) fuzzy synsets (T1 F-synsets) do not properly model the membership uncertainty, and propose an upgraded version of fuzzy synsets in which membership degrees of word-senses are represented by intervals, similar to what in Interval Type 2 Fuzzy Sets (IT2 FS) and discuss that IT2 FS theoretical framework is insufficient for analysis and design of such synsets, and propose a new concept, called Interval Probabilistic Fuzzy (IPF) sets. Then we present an algorithm for constructing the IPF synsets in any language, given a corpus and a word-sense-disambiguation system. Utilizing our algorithm and the open-American-online-corpus (OANC) and UKB word-sense-disambiguation, we constructed and published the IPF synsets of WordNet for English language.

Interval probabilistic fuzzy WordNet / Alizadeh-Q, Y.; Minaei-Bidgoli, B.; Hossayni, S.-A.; Akbarzadeh-T, M.-R.; Recupero, D.R.; Rajati, M.-R.; Gangemi, A.. - ELETTRONICO. - (2021).

Interval probabilistic fuzzy WordNet

Gangemi, A.
2021

Abstract

WordNet lexical-database groups English words into sets of synonyms called "synsets." Synsets are utilized for several applications in the field of text-mining. However, they were also open to criticism because although, in reality, not all the members of a synset represent the meaning of that synset with the same degree, in practice, they are considered as members of the synset, identically. Thus, the fuzzy version of synsets, called fuzzy-synsets (or fuzzy word-sense classes) were proposed and studied. In this study, we discuss why (type-1) fuzzy synsets (T1 F-synsets) do not properly model the membership uncertainty, and propose an upgraded version of fuzzy synsets in which membership degrees of word-senses are represented by intervals, similar to what in Interval Type 2 Fuzzy Sets (IT2 FS) and discuss that IT2 FS theoretical framework is insufficient for analysis and design of such synsets, and propose a new concept, called Interval Probabilistic Fuzzy (IPF) sets. Then we present an algorithm for constructing the IPF synsets in any language, given a corpus and a word-sense-disambiguation system. Utilizing our algorithm and the open-American-online-corpus (OANC) and UKB word-sense-disambiguation, we constructed and published the IPF synsets of WordNet for English language.
2021
Interval probabilistic fuzzy WordNet / Alizadeh-Q, Y.; Minaei-Bidgoli, B.; Hossayni, S.-A.; Akbarzadeh-T, M.-R.; Recupero, D.R.; Rajati, M.-R.; Gangemi, A.. - ELETTRONICO. - (2021).
Alizadeh-Q, Y.; Minaei-Bidgoli, B.; Hossayni, S.-A.; Akbarzadeh-T, M.-R.; Recupero, D.R.; Rajati, M.-R.; Gangemi, A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/916309
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