A divide-and-conquer genetic-fuzzy mining approach for items with multiple minimum supports

Chun Hao Chen*, Tzung Pei Hong, S. Tseng

*Corresponding author for this work

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

Since items may have their own characteristics, different minimum support values and membership functions may be specified for different items. In this paper, an enhanced approach is proposed, which processes the items in a divide-and-conquer strategy. The approach is designed for finding minimum support values, membership functions, and fuzzy association rules. Possible solutions are evaluated by their requirement satisfaction divided by their suitability of derived membership functions. The proposed GA framework maintains multiple populations, each for one item's minimum support value and membership functions. The final best minimum support values and membership functions in all the populations are then gathered together to be used for mining fuzzy association rules. Experimental results also show the effectiveness of the proposed approach.

原文English
主出版物標題2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
頁面1231-1235
頁數5
DOIs
出版狀態Published - 7 十一月 2008
事件2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008 - Hong Kong, China
持續時間: 1 六月 20086 六月 2008

出版系列

名字IEEE International Conference on Fuzzy Systems
ISSN(列印)1098-7584

Conference

Conference2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
國家China
城市Hong Kong
期間1/06/086/06/08

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