User tag weight assessment based on fuzzy theory in mobile social networks

Abstract

Mobile social network supports mobile communication and asynchronous social networking. For enterprises, how to provide better services and create greater business value through the data and information provided by users is crucial. For example, enterprises need to build user profiles to achieve personalized recommendation and precision marketing. In view of the data modeling stage of user profile, we propose a method to evaluate user tag weight, which includes two steps. Specifically, we introduce fuzzy theory to get the initial weight interval. Then, genetic algorithm with single point crossover is used to optimize user tag weight. Experiment results show that the proposed method has better performance than other three methods applied to recommendation system.