1. IIMB-
  2. Faculty Publications
  3. Conference / Seminar / Presentations / Lectures
  4. 2000-2009
Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/11890
DC FieldValueLanguage
dc.contributor.authorNatarajan, Rajesh
dc.contributor.authorShekar, B
dc.date.accessioned2020-04-27T06:32:51Z-
dc.date.available2020-04-27T06:32:51Z-
dc.date.issued2005
dc.identifier.isbn9781581139648
dc.identifier.urihttps://repository.iimb.ac.in/handle/2074/11890-
dc.description.abstractThe 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.
dc.publisherAssociation for Computing Machinery
dc.subjectAssociation rules
dc.subjectData mining
dc.subjectInterestingness
dc.subjectRelatedness
dc.titleA relatedness-based data-driven approach to determination of interestingness of association rules
dc.typePresentation
dc.relation.conference20th Annual ACM Symposium on Applied Computing: 13-17 March, 2005, Santa Fe, NM; United States
dc.relation.publicationProceedings of the ACM Symposium on Applied Computing-
dc.identifier.doi10.1145/1066677.1066803
dc.pages551-552p.
dc.vol.noVol.1-
Appears in Collections:2000-2009
Files in This Item:
File SizeFormat 
Shekar_ACM_2005_Vol.1_P.551-552.pdf127.95 kBAdobe PDFView/Open
Show simple item record

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.