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Interestingness measures for data mining: A survey

Authors:

Howard J. HamiltonAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 38, Issue 3

Pages 9 - es

https://doi.org/10.1145/1132960.1132963

Published: 30 September 2006 Publication History

Abstract

Interestingness measures play an important role in data mining, regardless of the kind of patterns being mined. These measures are intended for selecting and ranking patterns according to their potential interest to the user. Good measures also allow the time and space costs of the mining process to be reduced. This survey reviews the interestingness measures for rules and summaries, classifies them from several perspectives, compares their properties, identifies their roles in the data mining process, gives strategies for selecting appropriate measures for applications, and identifies opportunities for future research in this area.

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Index Terms

Interestingness measures for data mining: A survey
1. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 38, Issue 3

2006

129 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/1132960

Issue’s Table of Contents

Copyright © 2006 ACM.

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Published: 30 September 2006

Published in CSUR Volume 38, Issue 3

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