earticle

영어

Due to the huge information, short length and noise data, the traditional method has poor effect on micro-blog entity relationship modeling. In this paper, a new micro-blog user interests discovering approach based on tag is presented to improve the entity relationship modeling. First the matrix of user tag built by traditional way may generate the problem of sparse matrix in tag recommendation, so we introduce the information of micro-blog and establish the bipartite graph of User-Tag and Tag-Word respectively, then use them to recommend tag to micro-blog users. Meanwhile interactive relationship between users also show their interests, we establish a graph of tag relation by users’ relationship and propose a method called Tag Rank on the basis of this graph to improve the precision of the model. Finally, we combine the two methods to discover user interests. In the experiment, we use several measurement metrics: F-value, precision and the recall rate. It is proven that the new approach in the paper have a perfect performance.