Modeling Temporal Dynamics of User Interests in Online Social Networks

摘要: Abstract Recent years have witnessed an explosive growth of Online Social Networks (OSNs), which serve as a fertile ground for research such as, characterizing individual and group behaviors, identifying information diffusion patterns, building new recommendation system. This paper explores user interests in social network. While has been extensively studied the fundamental solution, it neglects point that may change her due to status shift over time. In this paper, we explore two main problems: how time whether hierarchy. To end, first formulate problem, then adopt semantic enrichment method determine interests, finally employ topic hierarchy tree model capture identify interest Experimental results demonstrate can be divided into primary secondary interest. hold stability long-term period; interest, however, is more likely keep up with hot topics or events moment. Meanwhile, We also test compare our existing systems - Who likes what? TUMS, result shows profiled fine-grained interests.