Data mining solutions for location and service request patterns in the mobile environment of distributed data sets

Abstract

The rapid advances in wireless and web technologies enable mobile users to request various kinds of services through mobile devices anytime and anywhere. Location-based services (LBS) integrate a mobile user s location with the services, to provide added value to the mobile users. For example, the mobile user is driving a car at location A and he/she submits a service request, find the nearest medical shops . Then he can move to another location B, where he can submit a service request, find the restaurants nearby . The main objective of this research work is to provide location based services to mobile users efficiently and quickly. This research is focused on the problem of providing location-based services to mobile users. This problem is composed of two major issues: mobility prediction and service request prediction. In this research work, the distributed Knowledge grid based Mobility Pattern Mining (KMPM) algorithm has been proposed to predict the next location of mobile users in a mobile environment, which provides better efficiency in terms of execution time and computational cost. This research work addressed the problems associated with the reexecution of the data mining algorithm. A new algorithm called the Distributed Pattern Miner (DPM) is developed for mining location aware service request patterns from databases on a data grid. This research work addressed the problem of deriving the new location and service request pattern in re-executing the algorithm fromscratch, resulting in excessive computation. A new algorithm called the Incremental Distributed Pattern Miner (IDPM) is proposed for mining location-aware service request patterns from databases on a data grid. The time taken to generate the location and service request patterns by the incremental mining algorithm, is lesser than that of the re-computing approach in terms of execution time. It has been found that both the service providers and the mobile users have been benefited from the data mining solutions provided in this research work. newline newline