Fast Borderline Association Mining

W.K. Chen, D. Baumgartner, and R. Millikin (USA)


Association Mining, Borderline Itemset.


In this paper, we present a modification to the AprioriBL algorithm, which is an extension to a well-known Asso ciation Mining algorithm, Apriori. AprioriBL targets the borderline cases of frequent itemsets; however, it performs poorly. Our new algorithm, AprioriBLT, considers only the borderline cases for generating itemsets. This increases performance at the cost of accuracy. A comparison is made between AprioriBL and AprioriBLT, and the efficacy of AprioriBLT is discussed.

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