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Liang Chen

16 papers hereh-index 284.7k citations66 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author12
  • last author2

Across the 16 of 16 papers where every author was matched, so the position is known.

fields
  • cs.LG6
  • cs.IR4
  • cs.AI2
  • cs.SE2
  • cs.CY1
  • cs.NE1
same name
  • Liang Chen — 25 papers, h 9
  • Liang Chen — 16 papers, h 8
  • Liang Chen — 16 papers, h 9
  • Liang Chen — 15 papers, h 11
  • Liang Chen — 11 papers, h 16
  • Liang Chen — 8 papers, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192023
most citedInteractive Path Reasoning on Graph for Conversational Recommendation

161 citations · 197 across the 15 of their papers we have counts for

collaborators
Showing cs.IRShow all

4 papers · 1 filter

cs.IR2021

Personalized Bundle Recommendation in Online Games

Qilin Deng, Kai Wang, Minghao Zhao +5

In business domains, \textit{bundling} is one of the most important marketing strategies to conduct product promotions, which is commonly used in online e-commerce and offline reta…

cs.IR2021★ 2 cited

Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation

Kai Wang, Zhene Zou, Qilin Deng +5

In recent years, there are great interests as well as challenges in applying reinforcement learning (RL) to recommendation systems (RS). In this paper, we summarize three key pract…

cs.IR2020★ 161 cited

Interactive Path Reasoning on Graph for Conversational Recommendation

Wenqiang Lei, Gangyi Zhang, Xiangnan He +4

Traditional recommendation systems estimate user preference on items from past interaction history, thus suffering from the limitations of obtaining fine-grained and dynamic user p…

cs.IR2019★ 3 cited

Data Poisoning Attacks on Neighborhood-based Recommender Systems

Liang Chen, Yangjun Xu, Fenfang Xie +2

Nowadays, collaborative filtering recommender systems have been widely deployed in many commercial companies to make profit. Neighbourhood-based collaborative filtering is common a…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.