The method of micro-blog article retrieval based on text similarity

With the growth of micro-blog users, the number of micro-blog text is also showing an explosive growth trend. Faced with such a large amount of text data, how to effectively retrieve useful information is very important for micro-blog users. This paper proposes a method combining traditional TF-IDF computing and LDA topic model. First, we compute by TF-IDF to find micro-blog articles about word frequency similarity. Then we use the LDA topic model approach to filter out micro-blog articles with similar themes. Experimental results show that using the integrated search method, users can retrieve more suitable user's actual needs micro-blog articles.