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主要題名:Pattern filtering and classification for market basket analysis with profit-based measures
作者姓名:Chen, Mu-ChenWu, Kuan-TingChao, Chuang-Min
貢獻者資料:管理學院/經營管理系
關鍵詞:data miningdecision treedata envelopment analysisassociation rulesprofit mining
論文中文摘要:Market basket analysis is one of the typical applications in mining association rules. The valuable
information discovered from data mining can be used to support decision making. Generally, support
and confidence (objective) measures are used to evaluate the interestingness of association rules. However, in
some cases, by using these two measures, the discovered rules may be not profitable and not actionable
(not interesting) to enterprises. Therefore, how to discover the patterns by considering both objective measures
(e.g. probability) and subjective measures (e.g. profit) is a challenge in data mining, particularly in marketing
applications. This paper focuses on pattern evaluation in the process of knowledge discovery by using the
concept of profit mining. Data Envelopment Analysis is utilized to calculate the efficiency of discovered
association rules with multiple objective and subjective measures. After evaluating the efficiency of association
rules, they are categorized into two classes, relatively efficient (interesting) and relatively inefficient
(uninteresting). To classify these two classes, Decision Tree (DT)-based classifier is built by using the
attributes of association rules. The DT classifier can be used to find out the characteristics of interesting
association rules, and to classify the unknown (new) association rules.
出版日期:2012-05
論文ID:11073-pa-cm-2012-05_1p
典藏單位:國立臺北科技大學
數位物件檔名:11073-pa-cm-2012-05_1p.pdf
統一資源識別號:http://dx.doi.org/10.1111/j.1468-0394.2010.00570.x
備註:©2011 Blackwell Publishing Ltd
資料開放狀態:開放
刊物名稱:Expert Systems
期數:29(2)
論文起迄頁碼:170-182