Search Results for author: Shaojian He

Found 3 papers, 1 papers with code

Multi-level Contrastive Learning Framework for Sequential Recommendation

no code implementations27 Aug 2022 Ziyang Wang, Huoyu Liu, Wei Wei, Yue Hu, Xian-Ling Mao, Shaojian He, Rui Fang, Dangyang Chen

Different from the previous contrastive learning-based methods for SR, MCLSR learns the representations of users and items through a cross-view contrastive learning paradigm from four specific views at two different levels (i. e., interest- and feature-level).

Contrastive Learning Relation +1

Learning User Representations with Hypercuboids for Recommender Systems

3 code implementations11 Nov 2020 Shuai Zhang, Huoyu Liu, Aston Zhang, Yue Hu, Ce Zhang, Yumeng Li, Tanchao Zhu, Shaojian He, Wenwu Ou

Furthermore, we present two variants of hypercuboids to enhance the capability in capturing the diversities of user interests.

Collaborative Filtering Recommendation Systems

Contextual-Bandit Based Personalized Recommendation with Time-Varying User Interests

no code implementations29 Feb 2020 Xiao Xu, Fang Dong, Yanghua Li, Shaojian He, Xin Li

A contextual bandit problem is studied in a highly non-stationary environment, which is ubiquitous in various recommender systems due to the time-varying interests of users.

Recommendation Systems

Cannot find the paper you are looking for? You can Submit a new open access paper.