Synthesizing global negative association rules in multi-database mining
Joint Authors
Hariharan, Shanmugasundaram
Selvamuthukumaran, Shanmugam
Ramkumar, Thirunavukkarasu
Source
The International Arab Journal of Information Technology
Issue
Vol. 11, Issue 6 (30 Nov. 2014)6 p.
Publisher
Publication Date
2014-11-30
Country of Publication
Jordan
No. of Pages
6
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
Association rule mining has been widely adopted by data mining community for discovering relationship among item-sets that co-occur together frequently.
Besides positive association rules, negative association rule mining, which find out negation relationships of frequent item-sets are also important.
The importance of negative association rule mining is accounted in customer-driven domains such as market basket analysis for identifying products that conflict with each other.
In multi-database mining context, mining negation relation among item-sets and synthesizing global negative association rules from multiple data sources located in different places are having importance in arriving decisions both at strategic and branch levels.
This paper made an attempt for synthesizing global negative association rules which are voted by most of the participating data sources while mining multiple data sources.
Experimental data are employed to test the theoretical analysis of the proposal using UCI machine learning repository data set.
The space and time complexity analysis presented in the paper show the efficiency of the proposed approach.
American Psychological Association (APA)
Ramkumar, Thirunavukkarasu& Hariharan, Shanmugasundaram& Selvamuthukumaran, Shanmugam. 2014. Synthesizing global negative association rules in multi-database mining. The International Arab Journal of Information Technology،Vol. 11, no. 6.
https://search.emarefa.net/detail/BIM-380120
Modern Language Association (MLA)
Selvamuthukumaran, Shanmugam…[et al.]. Synthesizing global negative association rules in multi-database mining. The International Arab Journal of Information Technology Vol. 11, no. 6 (Nov. 2014).
https://search.emarefa.net/detail/BIM-380120
American Medical Association (AMA)
Ramkumar, Thirunavukkarasu& Hariharan, Shanmugasundaram& Selvamuthukumaran, Shanmugam. Synthesizing global negative association rules in multi-database mining. The International Arab Journal of Information Technology. 2014. Vol. 11, no. 6.
https://search.emarefa.net/detail/BIM-380120
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-380120