A. Silberschatz et A. Tuzhilin, WHAT MAKES PATTERNS INTERESTING IN KNOWLEDGE DISCOVERY SYSTEMS, IEEE transactions on knowledge and data engineering, 8(6), 1996, pp. 970-974
Citations number
16
Categorie Soggetti
Information Science & Library Science","Computer Sciences, Special Topics","Engineering, Eletrical & Electronic","Computer Science Artificial Intelligence
One of the central problems in the field of knowledge discovery is the
development of good measures of interestingness of discovered pattern
s. Such measures of interestingness are divided into objective measure
s-those that depend only on the structure of a pattern and the underly
ing data used in the discovery process, and the subjective measures-th
ose that also depend on the class of users who examine the pattern. Th
e focus of this paper is on studying subjective measures of interestin
gness. These measures are classified into actionable and unexpected, a
nd the relationship between them is examined. The unexpected measure o
f interestingness is defined in terms of the belief system that the us
er has. Interestingness of a pattern is expressed in terms of how it a
ffects the belief system. The paper also discusses how this unexpected
measure of interestingness can be used in the discovery process.