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.
Copyright Date
January 2003
Publication Date
1-1-2003
Pagination
703-707p.
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