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A new method for similarity indexing of market basket data

Authors:

Charu C. Aggarwal,

Philip S. YuAuthors Info & Claims

ACM SIGMOD Record, Volume 28, Issue 2

Pages 407 - 418

https://doi.org/10.1145/304181.304218

Published: 01 June 1999 Publication History

Abstract

In recent years, many data mining methods have been proposed for finding useful and structured information from market basket data. The association rule model was recently proposed in order to discover useful patterns and dependencies in such data. This paper discusses a method for indexing market basket data efficiently for similarity search. The technique is likely to be very useful in applications which utilize the similarity in customer buying behavior in order to make peer recommendations. We propose an index called the signature table, which is very flexible in supporting a wide range of similarity functions. The construction of the index structure is independent of the similarity function, which can be specified at query time. The resulting similarity search algorithm shows excellent scalability with increasing memory availability and database size.

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Chander B(2020)Clustering and Bayesian NetworksHandbook of Research on Big Data Clustering and Machine Learning10.4018/978-1-7998-0106-1.ch004(50-73)Online publication date: 2020
https://doi.org/10.4018/978-1-7998-0106-1.ch004
Yang BMareboyana M(2012)Similarity search in sensor networks using semantic-based cachingJournal of Network and Computer Applications10.1016/j.jnca.2011.05.00835:2(577-583)Online publication date: 1-Mar-2012
https://dl.acm.org/doi/10.1016/j.jnca.2011.05.008
Zhang XChen KShou LChen GGao YTan K(2012)Efficient processing of probabilistic set-containment queries on uncertain set-valued dataInformation Sciences: an International Journal10.1016/j.ins.2012.02.004196(97-117)Online publication date: 1-Aug-2012
https://dl.acm.org/doi/10.1016/j.ins.2012.02.004
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Index Terms

A new method for similarity indexing of market basket data
1. Information systems
  1. Information retrieval
  2. Information systems applications
    1. Data mining

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Information & Contributors

Information

Published In

cover image ACM SIGMOD Record

ACM SIGMOD Record Volume 28, Issue 2

June 1999

599 pages

ISSN:0163-5808

DOI:10.1145/304181

Chairmen:
Susan Davidson
Univ. of Pennsylvania
,
Christos Faloutsos
Carnegie Mellon Univ.

Issue’s Table of Contents

SIGMOD '99: Proceedings of the 1999 ACM SIGMOD international conference on Management of data
June 1999
604 pages
ISBN:1581130848
DOI:10.1145/304182
Chairmen:
Susan B. Davidson
Univ. of Pennsylvania, Philidelphia
,
Christos Faloutsos
Carnegie Mellon Univ., Pittsburgh

Copyright © 1999 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 01 June 1999

Published in SIGMOD Volume 28, Issue 2

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Chander B(2020)Clustering and Bayesian NetworksHandbook of Research on Big Data Clustering and Machine Learning10.4018/978-1-7998-0106-1.ch004(50-73)Online publication date: 2020
https://doi.org/10.4018/978-1-7998-0106-1.ch004
Yang BMareboyana M(2012)Similarity search in sensor networks using semantic-based cachingJournal of Network and Computer Applications10.1016/j.jnca.2011.05.00835:2(577-583)Online publication date: 1-Mar-2012
https://dl.acm.org/doi/10.1016/j.jnca.2011.05.008
Zhang XChen KShou LChen GGao YTan K(2012)Efficient processing of probabilistic set-containment queries on uncertain set-valued dataInformation Sciences: an International Journal10.1016/j.ins.2012.02.004196(97-117)Online publication date: 1-Aug-2012
https://dl.acm.org/doi/10.1016/j.ins.2012.02.004
Roh JHwang SYi B(2012)Efficient bitmap-based indexing of time-based interval sequencesInformation Sciences: an International Journal10.1016/j.ins.2011.08.013194(38-56)Online publication date: 1-Jul-2012
https://dl.acm.org/doi/10.1016/j.ins.2011.08.013
Wang HWu C(2012)A strategy-oriented operation module for recommender systems in E-commerceComputers and Operations Research10.1016/j.cor.2010.03.01139:8(1837-1849)Online publication date: 1-Aug-2012
https://dl.acm.org/doi/10.1016/j.cor.2010.03.011
Agrawal PArasu AKaushik RElmagarmid AAgrawal D(2010)On indexing error-tolerant set containmentProceedings of the 2010 ACM SIGMOD International Conference on Management of data10.1145/1807167.1807267(927-938)Online publication date: 6-Jun-2010
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Tanaka AAtlam EMorita KTsukuda YFuketa MAoe J(2009)Relevant estimation among fields using field association wordsInternational Journal of Computer Applications in Technology10.1504/IJCAT.2009.02660535:2/3/4(296-306)Online publication date: 1-Jun-2009
https://dl.acm.org/doi/10.1504/IJCAT.2009.026605
Krishnapuram RKumar MBasak JJain V(2002)Soft Computing in E-CommerceAdvances in Soft Computing — AFSS 200210.1007/3-540-45631-7_61(450-458)Online publication date: 29-Jan-2002
https://doi.org/10.1007/3-540-45631-7_61
Thakur SBandyopadhyay SMandal J(2019)Product Prediction and Recommendation in Sustainable E-Commerce Using Association Rule Mining and K-Means ClusteringAdvanced Multi-Criteria Decision Making for Addressing Complex Sustainability Issues10.4018/978-1-5225-8579-4.ch012(254-266)Online publication date: 2019
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Saravanan MJyothi V(2014)A novel approach for sequential pattern mining by using genetic algorithm2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT)10.1109/ICCICCT.2014.6992971(284-288)Online publication date: Jul-2014
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