Actionable high-coherent-utility fuzzy itemset mining
學年 102
學期 1
出版（發表）日期 2014-01-09
作品名稱 Actionable high-coherent-utility fuzzy itemset mining
作品名稱（其他語言）
著者 Chen, Chun-hao
單位
出版者
著錄名稱、卷期、頁數 Soft Computing 18(12),　p.2413-2424
摘要 Many fuzzy data mining approaches have been proposed for finding fuzzy association rules with the predefined minimum support from quantitative transaction databases. Since each item has its own utility, utility itemset mining has become increasingly important. However, common problems with existing approaches are that an appropriate minimum support is difficult to determine and that the derived rules usually expose common-sense knowledge, which may not be interesting from a business point of view. This study thus proposes an algorithm for mining high-coherent-utility fuzzy itemsets to overcome problems with the properties of propositional logic. Quantitative transactions are first transformed into fuzzy sets. Then, the utility of each fuzzy itemset is calculated according to the given external utility table. If the value is larger than or equal to the minimum utility ratio, the itemset is considered as a high-utility fuzzy itemset. Finally, contingency tables are calculated and used for checking whether a high-utility fuzzy itemset satisfies four criteria. If so, it is a high-coherent-utility fuzzy itemset. Experiments on the foodmart and simulated datasets are made to show that the derived itemsets by the proposed algorithm not only can reach better profit than selling them separately, but also can provide fewer but more useful utility itemsets for decision-makers.
關鍵字 Fuzzy set;Utility fuzzy itemsets;High-coherent-utility fuzzy itemset;Membership function;Domain-driven data mining
語言 en
ISSN 1432-7643
期刊性質 國外
收錄於
產學合作
通訊作者
審稿制度 否
國別 DEU
公開徵稿
出版型式 ,電子版,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/112494 )