Frequent Pattern Mining plays an essential role in many data mining tasks that try to find interesting patterns from databases, such as association rules, correlations, sequences, episodes, classifiers and clusters. In this paper, we propose a new association rule mining algorithm called Hash Based Frequent Itemsets-Quadratic Probing(HBFI-QP) in which hashing technology is used to store the database in vertical data format. To avoid hash collision and primary clustering problem in hashing, quadratic probing technique is utilized in this proposed vertical hashing. The advantages of this new hashing technique are easy to compute the hash function, fast access of data and efficiency. This algorithm provides facilities to avoid unnecessary scans to the database. © EuroJournals Publishing, Inc. 2011.