Research of Improved Association Rule Algorithms (Apriori and FP-Growth)
Journal Title: International journal of Emerging Trends in Science and Technology - Year 2014, Vol 1, Issue 6
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.
Authors and Affiliations
Anju Gandhi
Keywords
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