What makes patterns interesting in knowledge discovery systems

被引：278

作者：

Silberschatz, A ^{[1
]}

Tuzhilin, A ^{[1
]}

机构：

[1] NYU,STERN SCH BUSINESS,DEPT INFORMAT SYST,NEW YORK,NY 10012

来源：

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING | 1996年 / 8卷 / 06期

基金：

美国国家科学基金会;

关键词：

measures of interestingness; patterns; actionability; unexpectedness; belief systems;

D O I：

10.1109/69.553165

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

One of the central problems in the field of knowledge discovery is the development of good measures of interestingness of discovered patterns. Such measures of interestingness are divided into objective measures-those that depend only on the structure of a pattern and the underlying data used in the discovery process, and the subjective measures-those that also depend on the class of users who examine the pattern. The focus of this paper is on studying subjective measures of interestingness. These measures are classified into actionable and unexpected, and the relationship between them is examined. The unexpected measure of interestingness is defined in terms of the belief system that the user has. Interestingness of a pattern is expressed in terms of how it affects the belief system. The paper also discusses how this unexpected measure of interestingness can be used in the discovery process.

引用

页码：970 / 974

页数：5

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