Probabilistic Support Prediction: Fast Frequent Itemset Mining in Dense Data
Muhammad Sadeequllah,
Azhar Rauf,
Saif Ur Rehman
et al.
Abstract:Frequent itemset mining (FIM) is a highly resource-demanding data-mining task fundamental to numerous data-mining applications. Support calculation is a frequently performed computation-intensive operation of FIM algorithms, whereas storing transactional data is memory-intensive. The FIM is even more resource-hungry for dense data than for sparse data. The rapidly growing size of datasets further exacerbates this situation and necessitates the design of out-of-the-box highly efficient solutions. This paper pro… Show more
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