Mining least relational patterns from multi relational tables

Authors:
Siti Hairulnita Selamat;Mustafa Mat Deris;Rabiei Mamat;Zuriana Abu Bakar
Affiliations:
Department of Computer Science, University College of Science and Technology, Kuala Terengganu, Malaysia;Faculty of Information Technology and Multimedia, College University Technology Tun Hussein Onn, Johor, Malaysia;Department of Computer Science, University College of Science and Technology, Kuala Terengganu, Malaysia;Department of Computer Science, University College of Science and Technology, Kuala Terengganu, Malaysia
Venue:
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Year:
2005

Citing 13
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Abstract

Existing mining association rules in relational tables only focus on discovering the relationship among large data items in a database. However, association rule for significant rare items that appear infrequently in a database but are highly related with other items is yet to be discovered. In this paper, we propose an algorithm called Extraction Least Pattern (ELP) algorithm that using a couple of predefined minimum support thresholds. Results from the implementation reveal that the algorithm is capable of mining rare item in multi relational tables.