Information Recommendation System Based on the Analysis of User Relationship and Micro- blogging Content Mining

Based on analysis of user relationship to create a user influence model. By means of collecting the user data of Sina Weibo, this thesis will analyse Weibo users relationship and the causes of customer relationship networks. By using the fuzzy comprehensive evaluation methods to determine the relationship between different factors that may affect user influence and propose a formula as well as construct the centre user's user influence model. Proposed the recommendation algorithm of micro-blogging information. In this paper, the existing information recommendation algorithms were reviewed and summarized some micro-blogging information recommended methods. On account of this, the thesis proposes another calculation method which is based on the user relationship and micro-blogging content analysis to make the Weibo information recommendation for centre audience, and verifies the effectiveness of this algorithm through the experimental results.