A Location Context Awareness Personalized Mobile Service Prediction Model and it’s Algorithm: Design and Implementation

With the expansion of mobile Internet, location-based services have become a hot spot in Internet industry. To improve the accuracy and efficiency of the location-based services discovery, researchers in web services recommendation area are still busy looking for method. In this paper, it proposes a LCAMSP model (Location Context Awareness Mobile Service Prediction, LCAMSP) under mobile Internet environment, aims to meet the exact personal requirements of users’ current location and preference. Then, the similar users’ grouping is also a important thread to predict the continuous movement for mobile users. Because each user has own preference, a dynamic calculation function for the weight of each attribute is discussed in this paper. Finally, taking the hotel reservation service as an example, a verification algorithm will be applied to measure the performance of LCAMSP method. With the premise of increasing limited time, the accuracy of LCAMSP algorithm is significantly improved under the mobile service environment.