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Self-Evolving Expert Systems based on Fuzzy Neural Network and RDB Inference Engine
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Jin Sung Kim (School of Business Administration, Jeonju University)
Vol. 9, No. 2, Page: 19 ~ 38
Keywords
Expert systems, Knowledge base, Data mining, Relational database, Relational database, Inference engine, Self-evolving expert systems
Abstract
In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.
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Self-Evolving Expert Systems based on Fuzzy Neural Network and RDB Inference Engine
김진성 (전주대학교 경영학부)
Cite this article
JIIS Style
Kim, J. S., , "Self-Evolving Expert Systems based on Fuzzy Neural Network and RDB Inference Engine", Journal of Intelligence and Information Systems, Vol. 9, No. 2 (2003), 19~38.

IEEE Style
Jin Sung Kim, "Self-Evolving Expert Systems based on Fuzzy Neural Network and RDB Inference Engine", Journal of Intelligence and Information Systems, vol. 9, no. 2, pp. 19~38, 2003.

ACM Style
Kim, J. S.,, 2003. Self-Evolving Expert Systems based on Fuzzy Neural Network and RDB Inference Engine. Journal of Intelligence and Information Systems. 9, 2, 19--38.
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@article{Kim:JIIS:2003:163,
author = {Kim, Jin Sung},
title = {Self-Evolving Expert Systems based on Fuzzy Neural Network and RDB Inference Engine},
journal = {Journal of Intelligence and Information Systems},
issue_date = {November 2003},
volume = {9},
number = {2},
month = Nov,
year = {2003},
issn = {2288-4866},
pages = {19--38},
url = {},
doi = {},
publisher = {Korea Intelligent Information System Society},
address = {Seoul, Republic of Korea},
keywords = { Expert systems, Knowledge base, Data mining, Relational database, Relational database, Inference engine and Self-evolving expert systems },
}
%0 Journal Article
%1 163
%A Jin Sung Kim
%T Self-Evolving Expert Systems based on Fuzzy Neural Network and RDB Inference Engine
%J Journal of Intelligence and Information Systems
%@ 2288-4866
%V 9
%N 2
%P 19-38
%D 2003
%R
%I Korea Intelligent Information System Society