Mining fuzzy association rules from questionnaire data

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题名:	Mining fuzzy association rules from questionnaire data
作者:	Chen,YL;Weng,CH
贡献者:	資訊管理研究所
关键词:	ALGORITHM
日期:	2009
上传时间:	2010-06-29 20:37:42 (UTC+8)
出版者:	中央大學
摘要:	Association rule mining is one of most popular data analysis methods that can discover associations within data, Association rule mining algorithms have been applied to various datasets, due to their practical usefulness. Little attention has been paid, however, on how to apply the association mining techniques to analyze questionnaire data. Therefore, this paper first identifies the various data types that may appear in a questionnaire. Then, we introduce the questionnaire data mining problem and define the rule patterns that can be mined from questionnaire data. A unified approach is developed based on fuzzy techniques so that all different data types can be handled in a uniform manner. After that, an algorithm is developed to discover fuzzy association rules from the questionnaire dataset. Finally, we evaluate the performance of the proposed algorithm, and the results indicate that our method is capable of finding interesting association rules that would have never been found by previous mining algorithms. (C) 2008 Elsevier B.V. All rights reserved.
關聯:	KNOWLEDGE-BASED SYSTEMS
显示于类别:	[資訊管理研究所] 期刊論文

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