A Brief Survey on Frequent Patterns Mining of Uncertain Data

Frequent pattern mining is the extraction of interested collection of items from dataset. Frequent Itemset mining plays an important role in the mining of various patterns and is in demand in many real life applications. When handling uncertain data U-Apriori, UF-growth, UFP-growth and PUF-growth are examples of well-known mining algorithms, which use the UF-tree, the UFP-tree and the PUF-tree respectively. However, these trees can be large, and thus degrade the mining performance. The researchers have proposed various algorithms like U-Apriori, UFgrowth, UH-mine, PUF-growth etc. In this paper, we are presenting depth analysis of algorithms of mining frequent patterns from uncertain datasets and discuss some problems associated with these algorithms in transactional databases.