High-Speed Similitude Retrieval for a Viewpoint-Based Similarity Discrimination System

Takashi YUKAWA; Kaname KASAHARA; Kazumitsu MATSUZAWA

High-Speed Similitude Retrieval for a Viewpoint-Based Similarity Discrimination System

Takashi YUKAWA, Kaname KASAHARA, Kazumitsu MATSUZAWA

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This paper proposes high-speed similitude retrieval schemes for a viewpoint-based similarity discrimination system (VB-SDS) and presents analytical and experimental performance evaluations. The VB-SDS, which contains a huge set of semantic definitions of commonly used words and computes semantic similarity between any two words under a certain viewpoint, promises to be a very important module in analogical and case-based reasoning systems that provide solutions under uncertainty. By computing and comparing similarities for all words contained in the system, the most similar word for a given word can be retrieved under a given viewpoint. However, the time this consumes makes the VB-SDS unsuitable for inference systems. The proposed schemes reduce search space based on the upper bound of a similarity calculation function to increase retrieval speed. An analytical evaluation shows the schemes can achieve a thousand-fold speedup and confirmed through experimental results for a VB-SDS containing about 40,000 words.

Publication: IEICE TRANSACTIONS on Information Vol.E80-D No.12 pp.1215-1220

Publication Date: 1997/12/25

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Category: Artificial Intelligence and Cognitive Science

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Takashi YUKAWA
Kaname KASAHARA
Kazumitsu MATSUZAWA

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Takashi YUKAWA, Kaname KASAHARA, Kazumitsu MATSUZAWA, "High-Speed Similitude Retrieval for a Viewpoint-Based Similarity Discrimination System" in IEICE TRANSACTIONS on Information, vol. E80-D, no. 12, pp. 1215-1220, December 1997, doi: .
Abstract: This paper proposes high-speed similitude retrieval schemes for a viewpoint-based similarity discrimination system (VB-SDS) and presents analytical and experimental performance evaluations. The VB-SDS, which contains a huge set of semantic definitions of commonly used words and computes semantic similarity between any two words under a certain viewpoint, promises to be a very important module in analogical and case-based reasoning systems that provide solutions under uncertainty. By computing and comparing similarities for all words contained in the system, the most similar word for a given word can be retrieved under a given viewpoint. However, the time this consumes makes the VB-SDS unsuitable for inference systems. The proposed schemes reduce search space based on the upper bound of a similarity calculation function to increase retrieval speed. An analytical evaluation shows the schemes can achieve a thousand-fold speedup and confirmed through experimental results for a VB-SDS containing about 40,000 words.
URL: https://global.ieice.org/en_transactions/information/10.1587/e80-d_12_1215/_p

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@ARTICLE{e80-d_12_1215,
author={Takashi YUKAWA, Kaname KASAHARA, Kazumitsu MATSUZAWA, },
journal={IEICE TRANSACTIONS on Information},
title={High-Speed Similitude Retrieval for a Viewpoint-Based Similarity Discrimination System},
year={1997},
volume={E80-D},
number={12},
pages={1215-1220},
abstract={This paper proposes high-speed similitude retrieval schemes for a viewpoint-based similarity discrimination system (VB-SDS) and presents analytical and experimental performance evaluations. The VB-SDS, which contains a huge set of semantic definitions of commonly used words and computes semantic similarity between any two words under a certain viewpoint, promises to be a very important module in analogical and case-based reasoning systems that provide solutions under uncertainty. By computing and comparing similarities for all words contained in the system, the most similar word for a given word can be retrieved under a given viewpoint. However, the time this consumes makes the VB-SDS unsuitable for inference systems. The proposed schemes reduce search space based on the upper bound of a similarity calculation function to increase retrieval speed. An analytical evaluation shows the schemes can achieve a thousand-fold speedup and confirmed through experimental results for a VB-SDS containing about 40,000 words.},
keywords={},
doi={},
ISSN={},
month={December},}

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TY - JOUR
TI - High-Speed Similitude Retrieval for a Viewpoint-Based Similarity Discrimination System
T2 - IEICE TRANSACTIONS on Information
SP - 1215
EP - 1220
AU - Takashi YUKAWA
AU - Kaname KASAHARA
AU - Kazumitsu MATSUZAWA
PY - 1997
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E80-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 1997
AB - This paper proposes high-speed similitude retrieval schemes for a viewpoint-based similarity discrimination system (VB-SDS) and presents analytical and experimental performance evaluations. The VB-SDS, which contains a huge set of semantic definitions of commonly used words and computes semantic similarity between any two words under a certain viewpoint, promises to be a very important module in analogical and case-based reasoning systems that provide solutions under uncertainty. By computing and comparing similarities for all words contained in the system, the most similar word for a given word can be retrieved under a given viewpoint. However, the time this consumes makes the VB-SDS unsuitable for inference systems. The proposed schemes reduce search space based on the upper bound of a similarity calculation function to increase retrieval speed. An analytical evaluation shows the schemes can achieve a thousand-fold speedup and confirmed through experimental results for a VB-SDS containing about 40,000 words.
ER -