UFIMT: an uncertain frequent itemset mining toolbox

In recent years, mining frequent itemsets over uncertain data has attracted much attention in the data mining community. Unlike the corresponding problem in deterministic data, the frequent itemset under uncertain data has two different definitions: the expected support-based frequent itemset and the probabilistic frequent itemset. Most existing works only focus on one of the definitions and no comprehensive study is conducted to compare the two different definitions. Moreover, due to lacking the uniform implementation platform, existing solutions for the same definition even generate inconsistent results. In this demo, we present a demonstration called as UFIMT (Uncertain Frequent Itemset Mining Toolbox) which not only discovers frequent itemsets over uncertain data but also compares the performance of different algorithms and demonstrates the relationship between different definitions. In this demo, we firstly present important techniques and implementation skills of the mi...

• Type: Journal
• Year: 2012
• Where: KDD
• Authors: Yongxin Tong, Lei Chen 0002, Philip S. Yu
• Keywords: Data Mining, Frequent Itemset Mining, Implementation Platform, KDD 2012, Uniform Implementation