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An Efficient Association Rule Mining Using the H-BIT Array Hashing Algorithm

Association Rule Mining (ARM) finds the interesting relationship between presences of various items in a given database. Apriori is the traditional algorithm for learning association rules. However, it is affected by number of database scan and higher generation of candidate itemsets. Each level of candidate itemsets requires separate memory locations. Hash Based Frequent Itemsets - Quadratic Probing (HBFI - QP) algorithm, which is based on hashing technique for mining the frequent itemsets. In order to stay away from collisions and primary clustering in hashing process, Quadratic Probing (QP) technique is used. Though the primary clustering and collisions are eliminated, secondary clustering is formed in all cases and the hash table occupies more space than the total number of items in the database.

Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE) Topic: Data Management Date Added: Jan 2013 Format: PDF

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