What makes patterns interesting in knowledge discovery systems

Author

Silberschatz, Avi ; Tuzhilin, Alexander

Author_Institution

Lucent Technol. Bell Labs., Murray Hill, NJ, USA

Volume

8

Issue

6

fYear

1996

fDate

12/1/1996 12:00:00 AM

Firstpage

970

Lastpage

974

Abstract

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 the 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

Keywords

belief maintenance; deductive databases; knowledge acquisition; actionable measure; belief system; discovery process; interestingness measurement; knowledge discovery systems; objective measures; subjective measures; underlying data; unexpected measure; Cities and towns; Costs; Data security; Information systems; Insurance; Medical services; Pattern recognition; State estimation;

fLanguage

English

Journal_Title

Knowledge and Data Engineering, IEEE Transactions on

Publisher

ieee

ISSN

1041-4347

Type

jour

DOI

10.1109/69.553165

Filename

553165