On subjective measures of interestingness in knowledge discovery 论文

1995引用 358
AI-based Problem Solving and PlanningLogic, Reasoning, and KnowledgeBayesian Modeling and Causal Inference

摘要

One of the central problems in the field of knowledge discovery is the development of good measures of in-terestingness of discovered patterns. Such measures of interestingness are divided into objective measures- those that depend only on the structure of a pat-tern 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 clas-sify 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. Inter-estingness of a pattern is expressed in terms of how it affects the belief system. 1