1991 Fiscal Year Final Research Report Summary
Development of a Fuzzy Information Retrieval System
| Project/Area Number |
01850086
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| Research Category |
Grant-in-Aid for Developmental Scientific Research
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| Allocation Type | Single-year Grants |
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| Research Field |
計測・制御工学
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| Research Institution | The University of Tokushima (1990-1991)
University of Tsukuba (1989) |
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Principal Investigator |
MIYAMOTO Sadaaki Univ. of Tokushima. Dept. of Information Science and Intelligent Systems, Professor, 工学部知能情報工学科, 教授 (60143179)
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| Co-Investigator(Kenkyū-buntansha) |
NOMOTO Kouhei Mitsubishi Electric Co. Electronics System Laboratory, Researcher, 情報電子研究所, 研究員
MIYAKE Teruhisa Univ. of Tsukuba, Institute of Information Sciences and Electronics, Research As, 電子・情報工学系, 助手 (60209880)
NAKAYAMA Kazuhiko Univ. of Tsukuba, Institute of Information Sciences and Electronics, Professor, 電子・情報工学系, 教授 (50091913)
IKEBE Yasuhiko Univ. of Tsukuba, Institute of Information Sciences and Electronics, Professor, 電子・情報工学系, 教授 (10114034)
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| Project Period (FY) |
1989 – 1991
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| Keywords | fuzzy information retrieval / fuzzy indices / similarity retrieval / fuzzy retrieval system / fuzzy retrieval filter / algorithms / fuzzy thesaurus / fuzzy set models |
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| Research Abstract |
The aim of the present research project is to develop a fuzzy information retrieval system for practical use. For this purpose, methodology of fuzzy retrieval, fast algorithms, and advanced functions of retrieval have been studied. Document databases with fuzzy indices and fuzzy thesaurs have been developed. Furthermore. fuzzy retrieval methods have been applied to similarity retrieval of pictures and a DNA database. More details of the results of the development are given in the following.
(1) Methodological development
Methods of fuzzy retrieval such as fuzzy association retrieval using fuzzy thesaurus, fuzzy filter retrieval that uses a prior weighting to documents according to each user's preference. and similarity retrieval using fuzzy propositional indices have been developed. Fast algorithms have been developed to each of these retrieval methods.
(2) System and database development
A fuzzy information retrieval system that includes all of the above retrieval functions has been developed. This system enables fuzzy retrieval of over 30, 000 document records. A fuzzy thesaurus has been developed for a large-scale database of practical use. A document database with fuzzy indices and a fuzzy thesaurus has also been developed.
(3) Applications
Fuzzy retrieval techniques have been applied to similarity retrieval of image databases. An experiental image database with a fuzzy propositional indices has been developed and similarity retrieval method using a fuzzy set model has been implemented. A similarity retrieval using a matching function based on a fuzzy set model has been developed for a DNA database and retrieval experiments have been performed.
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