223 citations · 361 across the 5 of their papers we have counts for
5 papers · 1 filter
Towards Hierarchical Policy Learning for Conversational Recommendation with Hypergraph-based Reinforcement Learning
Sen Zhao, Wei Wei, Yifan Liu +6
Conversational recommendation systems (CRS) aim to timely and proactively acquire user dynamic preferred attributes through conversations for item recommendation. In each turn of C…
Multi-level Contrastive Learning Framework for Sequential Recommendation
Ziyang Wang, Huoyu Liu, Wei Wei +5
Sequential recommendation (SR) aims to predict the subsequent behaviors of users by understanding their successive historical behaviors. Recently, some methods for SR are devoted t…
Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning
Ding Zou, Wei Wei, Ziyang Wang +4
Incorporating Knowledge Graphs (KG) into recommeder system has attracted considerable attention. Recently, the technical trend of Knowledge-aware Recommendation (KGR) is to develop…
Person-job fit estimation from candidate profile and related recruitment history with co-attention neural networks
Ziyang Wang, Wei Wei, Chenwei Xu +2
Existing online recruitment platforms depend on automatic ways of conducting the person-job fit, whose goal is matching appropriate job seekers with job positions. Intuitively, the…
Multi-level Cross-view Contrastive Learning for Knowledge-aware Recommender System
Ding Zou, Wei Wei, Xian-Ling Mao +4
Knowledge graph (KG) plays an increasingly important role in recommender systems. Recently, graph neural networks (GNNs) based model has gradually become the theme of knowledge-awa…