Markov based social user interest prediction

Abstract

In this paper, we propose a new approach to predict users’ interest eigenvalues based on multi-Markov chain model, which provides a better personalized service for the users timely. We first collect a dataset from Sina Weibo that includes 4613 users and more than 16 million messages; Then, preprocess data set to obtain users’ interest eigenvalues. After that, divide users into several categories and establish multi-Markov chain to predict users’ interest eigenvalues. Our experiments show that using multi-Markov model to predict users’ interest eigenvalues is feasible and efficient, and could predicting both long-term and short-term user interests based on a suitable selection of the initial state distribution, λ.