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Author Kangjai Lee ♦ Soochan Hwang ♦ Kyhyun Um ♦ Sungyul Park
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©1993
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Data mining ♦ Intelligent systems ♦ Information systems ♦ Computational intelligence ♦ Computer science ♦ Relational databases ♦ Computational complexity ♦ Information retrieval ♦ Indexing ♦ Computer industry
Abstract Case-based reasoning is to solve new problems by adapting previous solutions to old problems. As an alternative to rule-based reasoning, the extraction of similar examples from previous knowledge is very important for solving practical problems. In this paper, we propose a method to extract analogical information for efficient knowledge processing in an intelligent information system supported by relational database technology. At first, the method incrementally retrieves candidate analogical cases from the case base. Then, it selects more similar cases, based on the similarity between the problem and the candidate. The approach substantially reduces the computational complexity in knowledge processing of intelligent information systems such as expert systems.
Description Author affiliation: Dept. of Comput. Sci., Suwon Ind. Coll., Kyungki, South Korea (Kangjai Lee)
ISBN 0780312333
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1993-10-19
Publisher Place China
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 325.01 kB
Page Count 4
Starting Page 644
Ending Page 647


Source: IEEE Xplore Digital Library