Social recommendations play a crucial role in providing personalized services to users by leveraging social relationships and user sessions. Despite recent advancements, it still faces challenges in dealing with social inconsistency and the loss of critical semantic information in user-service interactions. To overcome these problems, an Evolving Graph Contrastive Learning for Socially-aware Recom...Show More
Recommendation systems play a crucial part in helping users efficiently obtain information based on users’ current preferences and discover their individual needs, but the existing works are deficient in terms of the evolution of users’ interests. In this paper, Graph Embedding with Service and User information (GESU) model is proposed to address the limitations of capturing users’ fresh interests...Show More
