MAXLEN-FI: AN ALGORITHM FOR MINING MAXIMUM- LENGTH FREQUENT ITEMSETS FAST
Keywords:Association rules, Frequent itemsets, Maximum length frequent itemsets.
AbstractAssociation rule mining, one of the most important and well-researched techniques of data mining. Mining frequent itemsets are one of the most fundamental and most time-consuming problems in association rule mining. However, real-world applications are often sufficient to mine a small representative subset of frequent itemsets with low computational cost in generating association rules – maximum-length frequent itemsets. Maximum-length frequent itemsets can be useful in many application domains. In this paper, we proposed an algorithm called MAXLEN-FI for mining maximum-length frequent itemsets fast using an array of co-occurrence items. Finally, we presented experimental results on both synthetic and real-life datasets, which showed that the proposed algorithm performed better than the existing algorithms.
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