Abstract
Conference Title: 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Conference Start Date: 2016, Aug. 18 Conference End Date: 2016, Aug. 21 Conference Location: San Francisco, CA, USA Stored data in database can hide some knowledge, which is interesting, useful to hidden knowledge discover. In this context, an algorithms number a frequent itemsets and association rules extraction were presented. Special feature of these algorithms is to generation a large number of rules, making their exploitation a difficult task. In this paper we will introduce a new algorithm for association rules extraction. Proposed solution is based on two points, namely: frequent itemset extraction, and from these, it extracts association rules.