A taxonomy-based approach to determining generic interestingness of association rules

Description

Items are related to each other either because of the generic category to which they belong or due to their usage contexts. We describe four notions of item-relatedness based on relationships existing between them using a taxonomy. We combine two of them to get a new measure of item relatedness. We compare and contrast this measure with a traditional taxonomy-based similarity measure. Interestingness of an association rule is then inversely proportional to the least-related item pair in the rule.

Publication Date

1-1-2003

DOI

10.1109/TENCON.2003.1273270

ISBN

780381629

Publisher

IEEE

Keywords

Knowledge acquisition, Formal languages, Mathematical models, Societies and institutions, World Wide Web, Trees (mathematics), Generic category, Generic interestingness, Taxonomy, Data mining

Sponsorship

IEEE Region 10

Conference

IEEE TENCON 2003: Conference on Convergent Technologies for the Asia-Pacific Region: 15-17 October, 2003, Bangalore, India

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