Interestingness measures for data mining: A survey

被引:611
作者
Geng, Liqiang [1 ]
Hamilton, Howard J. [1 ]
机构
[1] Univ Regina, Dept Comp Sci, Regina, SK S4S 0A2, Canada
关键词
algorithms; measurement; knowledge discovery; classification rules; interestingness measures; interest measures; summaries; association rules;
D O I
10.1145/1132960.1132963
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Interestingness measures play an important role in data mining, regardless of the kind of patterns being mined. These measures are intended for selecting and ranking patterns according to their potential interest to the user. Good measures also allow the time and space costs of the mining process to be reduced. This survey reviews the interestingness measures for rules and summaries, classifies them from several perspectives, compares their properties, identifies their roles in the data mining process, gives strategies for selecting appropriate measures for applications, and identifies opportunities for future research in this area.
引用
收藏
页数:32
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