A relatedness-based data-driven approach to determination of interestingness of association rules

Description

The presence of unrelated or weakly related item-pairs can help in identifying Interesting Association Rules (ARs) in a market basket. We introduce three measures for capturing the extent of mutual interaction, substitutive and complementary relationships between two items. Item-relatedness, a composite of these relationships, can help to rank interestingness of an AR. The approach presented, is intuitive and can complement and enhance classical objective measures of interestingness. Copyright 2005 ACM.

Publication Date

1-1-2005

DOI

10.1145/1066677.1066803

ISBN

978-1581139648

Publisher

Association for Computing Machinery

Keywords

Association rules, Data mining, Interestingness, Relatedness

Conference

20th Annual ACM Symposium on Applied Computing: 13-17 March, 2005, Santa Fe, NM; United States

This document is currently not available here.

Share

COinS