Mining fuzzy temporal association rules by item lifespans

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题名:	Mining fuzzy temporal association rules by item lifespans
作者:	Chun-Hao Chena;Guo-Cheng Lanb;Tzung-Pei Hong;Shih-Bin Lind
关键词:	Fuzzy set;Fuzzy data mining;Fuzzy temporal association rule;Item lifespan
日期:	2016-04
上传时间:	2017-12-22 02:10:12 (UTC+8)
出版者:	Elsevier BV
摘要:	Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. In real-world applications, transactions may contain quantitative values and each item may have a lifespan from a temporal database. In this paper, we thus propose a data mining algorithm for deriving fuzzy temporal association rules. It first transforms each quantitative value into a fuzzy set using the given membership functions. Meanwhile, item lifespans are collected and recorded in a temporal information table through a transformation process. The algorithm then calculates the scalar cardinality of each linguistic term of each item. A mining process based on fuzzy counts and item lifespans is then performed to find fuzzy temporal association rules. Experiments are finally performed on two simulation datasets and the foodmart dataset to show the effectiveness and the efficiency of the proposed approach.
關聯:	Applied Soft Computing 41, pp.265–274
DOI:	10.1016/j.asoc.2016.01.008
显示于类别:	[資訊工程學系暨研究所] 期刊論文

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