Evaluation of Embedded Vectors for Lexemes and Synsets Toward Expansion of Japanese WordNet

Daiki Ko, Koichi Takeuchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we discuss the possibility to expand Japanese WordNet using AutoExtend that can produce embedded vectors based on dictionary structure. Recently several kinds of NLP tasks showed that the distributed representations for words are effective, however, the word-embedded vectors constructed based on contexts of surrounded words would be difficult to discriminate meanings of a word because every vector is produced for a word. On the other hand, AutoExtend that can produce embedded vectors for meanings and concepts as well as words taking into account thesaurus structure of dictionary, has been proposed and applied into English WordNet. Thus, in this paper, we apply AutoExtend into a Japanese dictionary i.e., Japanese WordNet to construct embedded vectors for lexems and synsets as well as words taking into account thesaurus structure of Japanese WordNet. The experimental results show that embedded vectors constructed by AutoExtend can be helpful to find corresponding meanings for unregistered words in the dictionary.

Original languageEnglish
Title of host publicationComputational Linguistics - 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, Revised Selected Papers
EditorsLe-Minh Nguyen, Satoshi Tojo, Xuan-Hieu Phan, Kôiti Hasida
PublisherSpringer
Pages79-87
Number of pages9
ISBN (Print)9789811561672
DOIs
Publication statusPublished - 2020
Event16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019 - Hanoi, Viet Nam
Duration: Oct 11 2019Oct 13 2019

Publication series

NameCommunications in Computer and Information Science
Volume1215 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019
Country/TerritoryViet Nam
CityHanoi
Period10/11/1910/13/19

Keywords

  • AutoExtend
  • Japanese WordNet
  • Synsets

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

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