Please use this identifier to cite or link to this item:
https://repository.iimb.ac.in/handle/2074/11890
Title: | A relatedness-based data-driven approach to determination of interestingness of association rules | Authors: | Natarajan, Rajesh Shekar, B |
Keywords: | Association rules;Data mining;Interestingness;Relatedness | Issue Date: | 2005 | Publisher: | Association for Computing Machinery | Related Publication: | Proceedings of the ACM Symposium on Applied Computing | Conference: | 20th Annual ACM Symposium on Applied Computing: 13-17 March, 2005, Santa Fe, NM; United States | Abstract: | 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. | URI: | https://repository.iimb.ac.in/handle/2074/11890 | ISBN: | 9781581139648 | DOI: | 10.1145/1066677.1066803 |
Appears in Collections: | 2000-2009 |
Files in This Item:
File | Size | Format | |
---|---|---|---|
Shekar_ACM_2005_Vol.1_P.551-552.pdf | 127.95 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.