Seasonal based High Utility Item Set Mining

Utility mining is a flourishing trend in data mining area. The extraction of high utility itemset is the task of detecting interesting patterns, i.e. groups of items that generate high returns/profits in the customer transaction database. All most all utility mining works consists of two phase candidate generation approach that is however inefficient, most algorithms first generate candidate itemsets by overestimating their utilities, and subsequently compute the exact utilities of these candidates. These algorithms incur the problem that a very large number of candidates are generated, but most of the candidates are found out to be not high utility after their exact utilities are computed. Two phase approach degrades the performance due to the large number of candidates. Hence, this paper suggests a way to find high utility patterns in a single phase. Detecting of HUP in single phase with frequent customer purchase behavior at seasons is addressed in this paper. No seasonal information were provided previously, at times the profit of items would be decided under particular seasons which increases the utility of itemsets. We have to find out the high utility Itemset based on seasonal impact which effects the business strategies in single phase. The objective is to discover groups of items periodically purchased by customers and generate large profits to the sales revenue. An efficient algorithm called Seasonal High Utility Itemset Mining (SHM) is proposed to effectively enumerate all sets of high seasonal utility objects. The experimental results show that the SHM algorithm is efficient and can filter a large number of non-seasonal patterns to reveal only the desired seasoned high utility sets. Keywords- Utility Mining, HUP, Interesting patterns, SHM.