Shuqing Li

SSE-PT: Sequential Recommendation Via Personalized Transformer

2020

Temporal information is crucial for recommendation problems because user preferences are naturally dynamic in the real world. Recent advances in deep learning, especially the discovery of various attention mechanisms and newer architectures in addition to …

Multiple similarity collaborative filtering recommendation among users

2020 · IOP Conference Series Materials Science and Engineering

Abstract [Objective] Through the analysis of multiple similarity among users, the problem that the traditional user based collaborative filtering algorithm only uses a single similarity and leads to the decline of recommendation quality is solved. …