Comparison of Various Association Rule Mining Algorithm on Frequent Itemsets

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Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Big Data
Format: PDF
Association rule mining has attracted wide attention in both research and application area recently. Mining multilevel association rules is one of the most important branch of it. This paper introduces an improved apriori algorithm so called FP-growth algorithm that will help resolve two neck-bottle problems of traditional apriori algorithm and has more efficiency than original one. New FP tree method is provide how it affected multilevel association rules mining is discussed. Experimental result shows that the algorithm has mining efficiency in execution time, memory usage and cpu utilizations that most current one like apriori.
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