Viewpoint-Based Measurement of Semantic Similarity Between Words
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
Text
Kasahara et al. "Viewpoint-Based Measurement of Semantic Similarity Between Words." Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics, 1995.Markdown
[Kasahara et al. "Viewpoint-Based Measurement of Semantic Similarity Between Words." Pre-proceedings of the Fifth International Workshop on Artificial Intelligence and Statistics, 1995.](https://mlanthology.org/aistats/1995/kasahara1995aistats-viewpointbased/)BibTeX
@inproceedings{kasahara1995aistats-viewpointbased,
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},
year = {1995},
pages = {292-302},
volume = {R0},
url = {https://mlanthology.org/aistats/1995/kasahara1995aistats-viewpointbased/}
}