Viewpoint-Based Measurement of Semantic Similarity between Words

Kaname Kasahara, Kazumitsu Matsuzawa, Tsutomu Ishikawa, Tsukasa Kawaoka
Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics, PMLR R0:292-302, 1995.

Abstract

A method of measuring semantic similarity between words using a knowledgebase constructed automatically from machine-readable dictionaries is proposed. The method takes into consideration the fact that similarity changes depending on situation or context, which we call ’viewpoint’. A feature of the method is that certain parts of the overall concept of words, compared with each other, are emphasized by using the viewpoint when calculating the degree of similarity. Evaluation shows the proposed method, although based on a simply structured knowledge-base, is superior to other currently available methods.

Cite this Paper

BibTeX
@InProceedings{pmlr-vR0-kasahara95a, title = {Viewpoint-Based Measurement of Semantic Similarity between Words}, author = {Kasahara, Kaname and Matsuzawa, Kazumitsu and Ishikawa, Tsutomu and Kawaoka, Tsukasa}, booktitle = {Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics}, pages = {292--302}, year = {1995}, editor = {Fisher, Doug and Lenz, Hans-Joachim}, volume = {R0}, series = {Proceedings of Machine Learning Research}, month = {04--07 Jan}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/r0/kasahara95a/kasahara95a.pdf}, url = {https://proceedings.mlr.press/r0/kasahara95a.html}, abstract = {A method of measuring semantic similarity between words using a knowledgebase constructed automatically from machine-readable dictionaries is proposed. The method takes into consideration the fact that similarity changes depending on situation or context, which we call ’viewpoint’. A feature of the method is that certain parts of the overall concept of words, compared with each other, are emphasized by using the viewpoint when calculating the degree of similarity. Evaluation shows the proposed method, although based on a simply structured knowledge-base, is superior to other currently available methods.}, note = {Reissued by PMLR on 01 May 2022.} }
Endnote
%0 Conference Paper %T Viewpoint-Based Measurement of Semantic Similarity between Words %A Kaname Kasahara %A Kazumitsu Matsuzawa %A Tsutomu Ishikawa %A Tsukasa Kawaoka %B Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics %C Proceedings of Machine Learning Research %D 1995 %E Doug Fisher %E Hans-Joachim Lenz %F pmlr-vR0-kasahara95a %I PMLR %P 292--302 %U https://proceedings.mlr.press/r0/kasahara95a.html %V R0 %X A method of measuring semantic similarity between words using a knowledgebase constructed automatically from machine-readable dictionaries is proposed. The method takes into consideration the fact that similarity changes depending on situation or context, which we call ’viewpoint’. A feature of the method is that certain parts of the overall concept of words, compared with each other, are emphasized by using the viewpoint when calculating the degree of similarity. Evaluation shows the proposed method, although based on a simply structured knowledge-base, is superior to other currently available methods. %Z Reissued by PMLR on 01 May 2022.
APA
Kasahara, K., Matsuzawa, K., Ishikawa, T. & Kawaoka, T.. (1995). Viewpoint-Based Measurement of Semantic Similarity between Words. Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics, in Proceedings of Machine Learning Research R0:292-302 Available from https://proceedings.mlr.press/r0/kasahara95a.html. Reissued by PMLR on 01 May 2022.

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