An Efficient Knowledge Base Management Using Hybrid SOM 


Vol. 9,  No. 5, pp. 635-642, Oct.  2002
10.3745/KIPSTB.2002.9.5.635


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  Abstract

There is a rapidly growing demand for the intellectualization of information technology. Especially, in the area of KDD (Knowledge Discovery in Database) which should make an optimal decision of finding knowledge from a large amount of data, the demand is enormous. A large volume of Knowledge Base should be efficiently managed for a more intellectual choice. This study is proposing a Hybrid SOM for an efficient search and renewal of knowledge base, which combines a self-study nerve network, Self-Organization Map with a probable distribution theory in order to get knowledge needed for decision-making management from the Knowledge Base. The efficient knowledge base management through this proposed method is carried out by a stimulation test. This test confirmed that the proposed Hybrid SOM can manage with efficiency Knowledge Base.

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[IEEE Style]

K. B. Yoon, J. H. Choi, C. J. Wang, "An Efficient Knowledge Base Management Using Hybrid SOM," The KIPS Transactions:PartB , vol. 9, no. 5, pp. 635-642, 2002. DOI: 10.3745/KIPSTB.2002.9.5.635.

[ACM Style]

Kyung Bae Yoon, Jun Hyeog Choi, and Chang Jong Wang. 2002. An Efficient Knowledge Base Management Using Hybrid SOM. The KIPS Transactions:PartB , 9, 5, (2002), 635-642. DOI: 10.3745/KIPSTB.2002.9.5.635.

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