NDLI: A mining algorithm for fuzzy weighted association rules

Content Provider	IEEE Xplore Digital Library
Author	Bao-Yi Wang Shao-Min Zhang
Copyright Year	2003
Description	Author affiliation: Dept. of Comput. Sci. & Eng., North China Electr. Power Univ., Hebei, China (Bao-Yi Wang; Shao-Min Zhang)
Abstract	The association rule mining is an important research subject of knowledge discovery. Aiming at the common method of mining for attributes of quantitative type in database, we analyze the existing defects and put forward a method of applying fuzzy set theory to association rules mining. Due to the problem that each attribute's importance is different in specific purpose mining, we put forward a solution by assigning corresponding weight to attribute of different importance. Based on this idea, we put forward a mining algorithm using fuzzy weighted association rules and through the given experiment we testify the feasibility of the algorithm, and point out the existing defect of the algorithm demanding improvement in future.
Sponsorship	IEEE Systems Man and Cybernetics Tech. Committee on Cybernetics, Hebei Univ. Northwestern Polytechnical Univ
Starting Page	2495
Ending Page	2499
File Size	271754
Page Count	5
File Format	PDF
ISBN	0780381319
DOI	10.1109/ICMLC.2003.1259932
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-11-05
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Association rules Fuzzy sets Computer science Itemsets Transaction databases Knowledge engineering Power engineering and energy Electronic mail Data analysis
Content Type	Text
Resource Type	Article

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