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

Daiki Ko; Koichi Takeuchi

doi:10.1007/978-981-15-6168-9_7

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

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Computational Linguistics - 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, Revised Selected Papers
Editors	Le-Minh Nguyen, Satoshi Tojo, Xuan-Hieu Phan, Kôiti Hasida
Publisher	Springer
Pages	79-87
Number of pages	9
ISBN (Print)	9789811561672
DOIs	https://doi.org/10.1007/978-981-15-6168-9_7
Publication status	Published - 2020
Event	16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019 - Hanoi, Viet Nam Duration: Oct 11 2019 → Oct 13 2019

Publication series

Name	Communications in Computer and Information Science
Volume	1215 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019
Country	Viet Nam
City	Hanoi
Period	10/11/19 → 10/13/19

Keywords

AutoExtend
Japanese WordNet
Synsets

ASJC Scopus subject areas

Computer Science(all)
Mathematics(all)

Access to Document

10.1007/978-981-15-6168-9_7

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Ko, D., & Takeuchi, K. (2020). Evaluation of Embedded Vectors for Lexemes and Synsets Toward Expansion of Japanese WordNet. In L-M. Nguyen, S. Tojo, X-H. Phan, & K. Hasida (Eds.), Computational Linguistics - 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, Revised Selected Papers (pp. 79-87). (Communications in Computer and Information Science; Vol. 1215 CCIS). Springer. https://doi.org/10.1007/978-981-15-6168-9_7

Evaluation of Embedded Vectors for Lexemes and Synsets Toward Expansion of Japanese WordNet. / Ko, Daiki; Takeuchi, Koichi.

Computational Linguistics - 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, Revised Selected Papers. ed. / Le-Minh Nguyen; Satoshi Tojo; Xuan-Hieu Phan; Kôiti Hasida. Springer, 2020. p. 79-87 (Communications in Computer and Information Science; Vol. 1215 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ko, D & Takeuchi, K 2020, Evaluation of Embedded Vectors for Lexemes and Synsets Toward Expansion of Japanese WordNet. in L-M Nguyen, S Tojo, X-H Phan & K Hasida (eds), Computational Linguistics - 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, Revised Selected Papers. Communications in Computer and Information Science, vol. 1215 CCIS, Springer, pp. 79-87, 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, Hanoi, Viet Nam, 10/11/19. https://doi.org/10.1007/978-981-15-6168-9_7

Ko D, Takeuchi K. Evaluation of Embedded Vectors for Lexemes and Synsets Toward Expansion of Japanese WordNet. In Nguyen L-M, Tojo S, Phan X-H, Hasida K, editors, Computational Linguistics - 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, Revised Selected Papers. Springer. 2020. p. 79-87. (Communications in Computer and Information Science). https://doi.org/10.1007/978-981-15-6168-9_7

Ko, Daiki ; Takeuchi, Koichi. / Evaluation of Embedded Vectors for Lexemes and Synsets Toward Expansion of Japanese WordNet. Computational Linguistics - 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, Revised Selected Papers. editor / Le-Minh Nguyen ; Satoshi Tojo ; Xuan-Hieu Phan ; Kôiti Hasida. Springer, 2020. pp. 79-87 (Communications in Computer and Information Science).

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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.",

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N2 - 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.

AB - 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.

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

Abstract

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Conference

Keywords

ASJC Scopus subject areas

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