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researcher

Y. Zheng

17 papers hereh-index 151.8k citations26 works total

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

author position
  • first author7
  • middle author9

Across the 16 of 17 papers where every author was matched, so the position is known.

fields
  • cs.IR11
  • cs.SI2
  • cs.AI1
  • cs.CY1
  • cs.LG1
  • physics.soc-ph1
same name
  • Y. Zheng — 371 papers
  • Y. Zheng — 207 papers, h 67
  • Y. Zheng — 43 papers
  • Y. Zheng — 41 papers
  • Y. Zheng — 35 papers, h 22
  • Y. Zheng — 20 papers

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
20202026
most citedDGCN: Diversified Recommendation with Graph Convolutional Networks

132 citations · 332 across the 15 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.IR2022★ 1 cited

Mutual Harmony: Sequential Recommendation with Dual Contrastive Network

Guanyu Lin, Chen Gao, Yinfeng Li +6

With the outbreak of today's streaming data, the sequential recommendation is a promising solution to achieve time-aware personalized modeling. It aims to infer the next interacted…

cs.IR2022★ 25 cited

DVR: Micro-Video Recommendation Optimizing Watch-Time-Gain under Duration Bias

Yu Zheng, Chen Gao, Jingtao Ding +4

Recommender systems are prone to be misled by biases in the data. Models trained with biased data fail to capture the real interests of users, thus it is critical to alleviate the…

cs.IR2022★ 24 cited

Causal Inference in Recommender Systems: A Survey and Future Directions

Chen Gao, Yu Zheng, Wenjie Wang +3

Recommender systems have become crucial in information filtering nowadays. Existing recommender systems extract user preferences based on the correlation in data, such as behaviora…

cs.IR2022★ 119 cited

Disentangling Long and Short-Term Interests for Recommendation

Yu Zheng, Chen Gao, Jianxin Chang +4

Modeling user's long-term and short-term interests is crucial for accurate recommendation. However, since there is no manually annotated label for user interests, existing approach…

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