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2010 | OriginalPaper | Chapter
Boolean Algebra and Compression Technique for Association Rule Mining
Authors : Somboon Anekritmongkol, M. L. Kulthon Kasamsan
Published in: Advanced Data Mining and Applications
Publisher: Springer Berlin Heidelberg
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Association Rule represents a promising technique to find hidden patterns in database. The main issue about mining association rule in the large database. One of the most famous association rule learning algorithms is Apriori. Apriori algorithm is one of algorithms for generation of association rules. The drawback of Apriori Rule algorithm is the number of time to read data in the database equally number of each candidate were generated. Many research papers have been published trying to reduce the amount of time to read data from the database. In this paper, we propose a new algorithm that will work rapidly. Boolean Algebra and Compression technique for Association rule Mining (B-Compress) is applied to compress database and reduce the amount of times to scan database tremendously. Boolean Algebra combines, compresses, generates candidate itemset and counts the number of candidates. The construction method of B-Compress has ten times higher mining efficiency in execution time than Apriori Rule.