A dynamic graph Hawkes process based on linear complexity self-attention for dynamic recommender systems

ABSTRACT: The dynamic recommender system realizes the real-time recommendation for users by learning the dynamic interest characteristics, which is especially suitable for the scenarios of rapid transfer of user interests, such as e-commerce and social media. The dynamic recommendation model mainly depends on the user-item history interaction sequence with timestamp, which contains historical records that reflect changes in the true interests of users and the popularity of items. Previous methods usually model interaction sequences to learn the dynamic embedding of users and items. However, these methods can not directly capture the excitation effects of different historical information on the evolution process of both sides of the interaction, i.e., the ability of events to influence the occurrence

SUBMITTER: Hou Z 

PROVIDER: S-EPMC10280484 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature