Abstract
Mobile web services pattern mining is an emerging field today, in which utility is playing an important role. Utility may be the profit, cost or price of an item. In the case of mobile web services, accessed preference is considered as a utility. With the help of utility mining, one can extract highly interesting frequent patterns of mobile web services. In previous related studies, most of the approaches use utility as an essential parameter to discover interesting patterns, but they also generate a large number of uninteresting patterns too. Another problem is related to computational time; because no filtration is applied and computational time is too much. In this paper, an efficient approach, Utility Based Frequent Pattern Mining, is proposed. It extracts utility based frequent patterns with high filtration in less computing time. The experimental results show that the proposed approach has good performance in terms of execution efficiency and memory utilization.