A Novel J2ME Service for Mining Incremental Patterns in Mobile Computing

Abstract

Data mining services play an important role in the telecommunications industry. Considering the importance of data mining services to provide intelligence locally on devices on mobile environments, we propose a data mining service that adopts the embedded data mining algorithm according to situation. In this paper, we propose a novel data mining algorithm named J2ME-based Mobile Progressive Pattern Mine (J2MPP-Mine) for effective mobile computing. In J2MPP-Mine, we first propose a subset finder strategy named Subset-Finder (S-Finder) to find the possible subsets for prune. Then, we propose a Subset pruner algorithm (SB-Pruner) for determining the frequent pattern. Furthermore, we proposed the novel prediction strategy to determine the superset and remove the subset which generates a less number of sets due to different filtering pruning strategy. Finally, through the simulation our proposed methods were shown to deliver excellent performance in terms of efficiency, accuracy and applicability under various system conditions. © Springer-Verlag Berlin Heidelberg 2010.