An on-line interactive method for finding association rules data streams

Se Jung Shin, Won Suk Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

In order to trace the changes of association rules over an online data stream efficiently, this paper proposes two different methods of generating all association rules directly over the changing set of currently frequent itemsets. While all of the currently frequent itemsets are monitored by the estDec method, all the association rules of every frequent itemset in the prefix tree of the estDec method are generated. For this purpose, a traversal stack is introduced to efficiently enumerate all association rules. These online methods can avoid the drawbacks of the conventional two-step approach. In an on-line environment, a user may be interested in finding those association rules whose antecedents or consequents are fixed to be a specific itemset. Since generating all the association rules may take too long to produce them timely, two additional methods, namely Assoc-X and Assoc-Y, are introduced. Finally, the proposed methods are compared by a series of experiments to identify their various characteristics.

Original languageEnglish
Title of host publicationCIKM 2007 - Proceedings of the 16th ACM Conference on Information and Knowledge Management
Pages963-966
Number of pages4
DOIs
Publication statusPublished - 2007 Dec 1
Event16th ACM Conference on Information and Knowledge Management, CIKM 2007 - Lisboa, Portugal
Duration: 2007 Nov 62007 Nov 9

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other16th ACM Conference on Information and Knowledge Management, CIKM 2007
CountryPortugal
CityLisboa
Period07/11/607/11/9

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All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

Cite this

Shin, S. J., & Lee, W. S. (2007). An on-line interactive method for finding association rules data streams. In CIKM 2007 - Proceedings of the 16th ACM Conference on Information and Knowledge Management (pp. 963-966). (International Conference on Information and Knowledge Management, Proceedings). https://doi.org/10.1145/1321440.1321586