An improved user interest modelling by considering user social relationship. Issue 3 (2nd May 2022) - Wang, Yanru
User interest modelling has always been an important direction in the research of microblog social network. In previous studies, people paid more attention to the expansion of tags from microblog short texts, but ignored the information contained in the relationship between users. We improved the user interest model based on multi-tag semantic correlation by considering user social relationship (MTSC-SR). This model is built on the basis of the previous improved microblog user-tag matrix and integrates the social similarity matrix of users. The construction of user social similarity matrix is used to represent the similarity of two users by considering the static and dynamic interest information of users. We verify the validity of our method through experiments, and the data set is captured by the open API. The results show that the proposed algorithm has good performance in extracting users' interest features.