"Fuzzy association rule mining based frequent pattern extraction from uncertain data"
Frequent pattern mining is one of the most important research topics for many real life applications in the area of data mining. Frequent item set originates from association rule mining that uses to find association rules of items in large transactional database. Many existing algorithm to mine for the frequent itemset from static transaction database that is definite known and precise. In this paper we conducted a study on uncertain data and fuzzy association rule mining approach. The main contribution of this paper is three manifolds. First we presented a review on existing method for finding frequent patterns form uncertain data. Second a new approach is proposed for finding frequent patterns from uncertain data, and third, the experiments are carried out to evaluate the performance of proposed approach for uncertain data. In this approach we have used fuzzy concept and originate the frequent patterns. The experimental results from the survey demonstrate that this proposed approach for valuable frequent pattern set the influential uncertain data mining.
2012 World Congress on Information and Communication Technologies