Frequent itemsets mining on weighted uncertain data
Manal Alharbi, Sudipta Pathak, Sanguthevar Rajasekaran · 2014
Mining frequent itemsets from datasets is a well studied problem. Several variations of this problem have also been investigated in the literature. Two such variations deal with datasets with weights and datasets with uncertainty. There are many applications where the data are both weighted and uncertain. Mining from such datasets has not been studied before. In this paper we initiate the study of frequent itemsets mining from weighted uncertain data. In particular, we propose two algorithms called HWUAPRIORI and VWUFIM for mining frequent itemsets from weighted uncertain data. We evaluate the performance of the proposed algorithms on various datasets.