What makes patterns interesting in knowledge discovery systems

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Silberschatz, A., Tuzhilin, A.: What makes patterns interesting in knowledge discovery systems. IEEE Trans. Knowl. Data Eng. 8(6), 970–974 (1996)




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

Extended Abstract


author={A. Silberschatz and A. Tuzhilin},
journal={IEEE Transactions on Knowledge and Data Engineering},
title={What makes patterns interesting in knowledge discovery systems},
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},
url={http://dx.doi.org/10.1109/69.553165 http://de.evo-art.org/index.php?title=What_makes_patterns_interesting_in_knowledge_discovery_systems},

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