Boolean Algebra and Compression Technique for Association Rule Mining
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 item-set and counts the number of candidates. The construction method of B-Compress has ten times higher mining efficiency in execution time than Apriori Rule.
Association rule Apriori Rule Boolean algebra Data mining
Somboon Anekritmongkol M.L. Kulthon Kasamsan
Faculty of information Technology, Rangsit University,Pathumtani 12000, Thailand
国际会议
6th International Conference on Advanced Data Mining and Applications(第六届先进数据挖掘及应用国际会议 ADMA 2010)
重庆
英文
150-157
2010-11-19（万方平台首次上网日期，不代表论文的发表时间）