402 citations · 1.1k across the 59 of their papers we have counts for
6 papers · 1 filter
Multi-grained Hypergraph Interest Modeling for Conversational Recommendation
Chenzhan Shang, Yupeng Hou, Wayne Xin Zhao +2
Conversational recommender system (CRS) interacts with users through multi-turn dialogues in natural language, which aims to provide high-quality recommendations for user's instant…
Towards Universal Sequence Representation Learning for Recommender Systems
Yupeng Hou, Shanlei Mu, Wayne Xin Zhao +3
In order to develop effective sequential recommenders, a series of sequence representation learning (SRL) methods are proposed to model historical user behaviors. Most existing SRL…
ID-Agnostic User Behavior Pre-training for Sequential Recommendation
Shanlei Mu, Yupeng Hou, Wayne Xin Zhao +2
Recently, sequential recommendation has emerged as a widely studied topic. Existing researches mainly design effective neural architectures to model user behavior sequences based o…
Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning
Yang Deng, Yaliang Li, Fei Sun +2
Conversational recommender systems (CRS) enable the traditional recommender systems to explicitly acquire user preferences towards items and attributes through interactive conversa…
RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms
Wayne Xin Zhao, Shanlei Mu, Yupeng Hou +16
In recent years, there are a large number of recommendation algorithms proposed in the literature, from traditional collaborative filtering to deep learning algorithms. However, th…
Sequential Recommendation with Self-Attentive Multi-Adversarial Network
Ruiyang Ren, Zhaoyang Liu, Yaliang Li +4
Recently, deep learning has made significant progress in the task of sequential recommendation. Existing neural sequential recommenders typically adopt a generative way trained wit…