Research of Improved Association Rule Algorithms (Apriori and FP-Growth)
International Journal of Emerging Trends in Science and Technology,
Vol. 1 No. 06 (2014),
1 August 2014
Abstract
Abstract: - Association rule mining explores interesting relationships among items in a given data set. An objective of association rule mining is to develop a systematic method using the given database and finds relationships between the different items. Goal of association rules finding associations among items from a set of transactions, which contain a set of items. In this paper we focused on explaining the fundamentals of association mining and analyze implementations of the well-known association rule algorithms. Study focuses on algorithms Apriori, FP-Growth, and Dynamic Itemset Counting. Moreover, the algorithm generates frequent item sets in order so that the result can be used expediently.
Key Terms – Association Rule Mining, FP-Growth Algorithm, Apriori algorithm, Frequent Itemsets.How to Cite
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References
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