The Interestingness of The Non-Interestingness Objection to General Jurisprudence

The, Interestingness of Deviations

One of the moet promising areas in Knowledge Discovery in Databases is the automatic analysis of changes and deviations. Several systems have recently been developed for this task. Suc~ of these systems hinges on their ability to identify s few important and relevant deviations among the multitude of potentially interesting events:~ In this paper we argue that related deviations should be group...

A General Measure of Rule Interestingness

Heuristic Measures of Interestingness

The tuples in a generalized relation (i.e., a summary generated from a database) are unique, and therefore, can be considered to be a population with a structure that can be described by some probability distribution. In this paper, we present and empirically compare sixteen heuristic measures that evaluate the structure of a summary to assign a single real-valued index that represents its inte...

Evaluating the Interestingness of Characteristic Rules

Knowledge Discovery Systems can be used to generate classification rules describing data from databases. Typically, only a small fraction of the rules generated may actually be of interest. Measures of rule intemstingness allow us to filter out less interesting rules. Classification rules may be discriminant (e + h) or characteristic (h + e), where e is evidence, and h is an hypothesis. For dis...

On rule interestingness measures

This paper discusses several factors influencing the evaluation of the degree of interestingness of rules discovered by a data mining algorithm. The main goals of this paper are: (1) drawing attention to several factors related to rule interestingness that have been somewhat neglected in the literature; (2) showing some ways of modifying rule interestingness measures to take these factors into ...