Fast tree-based mining of frequent itemsets from uncertain data

Abstract

Over the past two decades, numerous algorithms have been proposed for mining frequent itemsets from precise data. However, there are situations in which data are uncertain. In recent years, tree-based algorithms have been proposed to mine frequent itemsets from uncertain data. While the key success of tree-based algorithms for mining precise data is due to the compactness of a tree structure in capturing precise data, the corresponding tree structure in capturing uncertain data may not be so compact. In this paper, we propose a novel tree structure for capturing uncertain data such that it is as compact as the tree for capturing precise data. Moreover, we also propose two fast algorithms that use this compact tree structure to mine frequent itemsets. Experimental results showed the compactness of our tree and the effectiveness of our algorithms in mining frequent itemsets from uncertain data. © 2012 Springer-Verlag.