activity
20172023
most citedVariational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation

43 citations · 109 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IR2023

A Self-Correcting Sequential Recommender

Yujie Lin, Chenyang Wang, Zhumin Chen +6

Sequential recommendations aim to capture users' preferences from their historical interactions so as to predict the next item that they will interact with. Sequential recommendati…

cs.AI2022★ 43 cited

Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation

Xiaoyu Zhang, Xin Xin, Dongdong Li +5

Conversational recommender systems (CRSs) often utilize external knowledge graphs (KGs) to introduce rich semantic information and recommend relevant items through natural language…

cs.IR2022★ 39 cited

On the User Behavior Leakage from Recommender System Exposure

Xin Xin, Jiyuan Yang, Hanbing Wang +6

Modern recommender systems are trained to predict users potential future interactions from users historical behavior data. During the interaction process, despite the data coming f…

cs.IR2022★ 5 cited

Rethinking Reinforcement Learning for Recommendation: A Prompt Perspective

Xin Xin, Tiago Pimentel, Alexandros Karatzoglou +3

Modern recommender systems aim to improve user experience. As reinforcement learning (RL) naturally fits this objective -- maximizing an user's reward per session -- it has become…

cs.LG2021

Supervised Advantage Actor-Critic for Recommender Systems

Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis +1

Casting session-based or sequential recommendation as reinforcement learning (RL) through reward signals is a promising research direction towards recommender systems (RS) that max…

cs.SI2021★ 10 cited

Extracting Attentive Social Temporal Excitation for Sequential Recommendation

Yunzhe Li, Yue Ding, Bo Chen +5

In collaborative filtering, it is an important way to make full use of social information to improve the recommendation quality, which has been proved to be effective because user…

astro-ph.IM2017★ 12 cited

Pulsar Candidate Identification with Artificial Intelligence Techniques

Ping Guo, Fuqing Duan, Pei Wang +3

Discovering pulsars is a significant and meaningful research topic in the field of radio astronomy. With the advent of astronomical instruments such as he Five-hundred-meter Apertu…