Vector Similarity of Related Words and Synonyms in the Japanese WordNet

Takuya Hirao; Takahiko Suzuki; Nao Wariishi; Sachio Hirokawa

doi:10.52731/iee.v1.i4.20

Takuya Hirao Kyushu University
Takahiko Suzuki Kyushu University, Japan http://orcid.org/0000-0002-0153-6865
Nao Wariishi Kyushu University
Sachio Hirokawa Kyushu University

DOI: https://doi.org/10.52731/iee.v1.i4.20

Keywords: Decision tree, Thesaurus, Word2vec, WordNet

Abstract

Word2vec is a tool that produces vector representations of words from a large amount of text data. In this study, we show that only a part of the vector space produced by word2vec is sufficient to represent the collective sense of a set of related words in Japanese WordNet. Furthermore, we show that there is a subspace of the vector space that does not relate to the collective sense of related words and synonyms. We construct a compact decision tree by using the vectors to distinguish whether a given word belongs to the set of related words.

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