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A Framework for Weighted Association Rule Mining from Boolean and Fuzzy Data

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2 Author(s)
Li Guang-yuan ; Sch. of Comput. & Inf. Eng., Guangxi Teachers Educ. Univ., Nanning, China ; Hu Qin-bin

Association rules mining is one of the most important tasks in the field of data mining. It aims at searching for interesting relationship among items in a large data set. In this paper, we present a novel approach for mining the fuzzy weighted association rule from boolean and fuzzy data in large data set, where a weighted value is assigned to each item, we develop a novel approach to calculate the support and confidence of the weighted items, experimental results show that the proposed method is efficient and scalable.

Published in:

Internet Technology and Applications (iTAP), 2011 International Conference on

Date of Conference:

16-18 Aug. 2011