A Tag Probability Correlation Based Microblog Recommendation Method

Abstract

In order to improve users' experience it is necessary to recommend valuable and interesting content for users. A tag probability correlation based microblog recommendation method TPCMR is presented via analyzing microblog features and the deficiencies of existing microblog recommendation algorithm. Firstly, our method takes advantage of the probability correlation between tags to construct the tag similarity matrix. Then the weight of the tag for each user is enhanced based on the relevance weighting scheme and the user tag matrix can be constructed. The matrix is updated using the tag similarity matrix, which contains both the user interest information and the relationship between tags and tags. Experimental results show that the algorithm is effective for microblog recommendation.