Integration of K-means algorithm and AprioriSome algorithm for fuzzy sequential pattern mining

R. J. Kuo; C. M. Chao; C. Y. Liu

doi:10.1016/j.asoc.2008.03.010

Integration of K-means algorithm and AprioriSome algorithm for fuzzy sequential pattern mining

R. J. Kuo
, C. M. Chao
, C. Y. Liu

經營管理系

研究成果: 期刊貢獻 › 文章 › 同行評審

15 引文斯高帕斯（Scopus）

摘要

Since Agrawal and Srikant proposed sequential pattern mining in 1995, there have been many scholars working to improve the efficiency and reduce the processing time of algorithms. This study intends to propose a fuzzy AprioriSome algorithm for fuzzy sequential patterns mining with integration with clustering technique, K-means algorithm. Two experiments performed using transaction data provided by a securities firm and foodmarket data from SQL sever 2000 demonstrate the strength of fuzzy AprioriSome sequential pattern mining in mining large quantity of transaction data.

原文	English
頁（從 - 到）	85-93
頁數	9
期刊	Applied Soft Computing Journal
卷	9
發行號	1
DOIs	https://doi.org/10.1016/j.asoc.2008.03.010
出版狀態	Published - 1月 2009

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10.1016/j.asoc.2008.03.010

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Integration of K-means algorithm and AprioriSome algorithm for fuzzy sequential pattern mining

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