NDLI: Decision logics for knowledge representation in data mining

Content Provider	IEEE Xplore Digital Library
Author	Tuan-Fang Fan Wu-Chih Hu Churn-Jung Liau
Copyright Year	2001
Description	Author affiliation: Dept. of Inf. Eng., Nat. Penghu Inst. of Technol., Taiwan (Tuan-Fang Fan)
Abstract	In this paper the qualitative and quantitative semantics for rules in data tables are investigated from a logical viewpoint. In modern data analysis, knowledge can be discovered from data tables and is usually represented by some rules. However the knowledge is useful for a human user only when he can understand the meaning of the rules. This is called the interpretability problem of intelligent data analysis. The solution of the problem depends on the selection of the rule representation language. A good representation language should have clear semantics so that a rule can be effectively validated with respect to the given data tables. In this regard, logic is one of the best choices. Starting from reviewing the decision logic for data tables, we subsequently generalize it to fuzzy and possibilistic decision logics. The rules are then viewed as the implications between well-formed formulas of these logics and their semantics with respect to precise or uncertain data tables are presented. The validity, support, and confidence of a rule are also rigorously defined in the framework.
Sponsorship	IEEE Comput. Soc
Starting Page	626
Ending Page	631
File Size	540878
Page Count	6
File Format	PDF
ISBN	0769513727
ISSN	07303157
DOI	10.1109/CMPSAC.2001.960678
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-10-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knowledge representation Data mining Data analysis Humans Fuzzy logic Modems Data engineering Information science Artificial intelligence Information retrieval
Content Type	Text
Resource Type	Article
Subject	Computer Science Applications Software

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