On Subjective Measures of Interestingness in Knowledge Discovery

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 purpose of this paper is to lay the groundwork for a comprehensive study of subjective measures of interestingness. In the paper, we classify these measures into actionable and unexpected, and examine the relationship between them. 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.

• Type: Conference
• Year: 1995
• Where: KDD
• Authors: Abraham Silberschatz, Alexander Tuzhilin
• Keywords: Data Mining, KDD 1995, Objective Measures, Subjective Measures, Such Measures