Hybrid search based association rule mining

Ahmed Ghanem; Hamed M. Sallam

doi:10.1109/pacrim.2011.6032963

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JOURNAL ARTICLE

Hybrid search based association rule mining

Ahmed Ghanem Hamed M. Sallam

Year: 2011 Vol: 90 Pages: 608-612

DOI: 10.1109/pacrim.2011.6032963

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Abstract

Association rule mining algorithms provide different search strategies to discover the frequent itemsets; however the problem of large search space is still hard to handle. The present paper suggests a novel hybrid search technique based on reducing the search space, I/O, and CPU times. This can improve the performance up to several orders of magnitude compared to APRIORI algorithm.

Keywords:

Association rule learning Computer science Data mining Apriori algorithm A priori and a posteriori Space (punctuation) Search algorithm Association (psychology) Machine learning Algorithm

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Topics

Data Mining Algorithms and Applications

Physical Sciences → Computer Science → Information Systems

Rough Sets and Fuzzy Logic

Physical Sciences → Computer Science → Computational Theory and Mathematics

Data Management and Algorithms

Physical Sciences → Computer Science → Signal Processing

Hybrid search based association rule mining

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