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Association rule mining along with frequent items has been comprehensively research in data mining. In this paper, we proposed a model for association rules to mine the generated frequent k-itemset. We take this process as extraction of rules which expressed most useful information. Therefore, transactional knowledge of using websites is considered to solve the purpose. In this paper we use interestingness...
In this paper, we determine the empirical comparison of Apriori and FP-growth algorithm for frequent item set sequences for Web Usage data. We define the data structure, its implementation and algorithmic features mainly focusing on those that also arise in frequent item set mining. Web usage mining itself can be defined further depending on the type of usage data is considered like web server data,...
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