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Hongzhi Yin

14 papers hereh-index 586 citations16 works total

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

author position
  • middle author2
  • last author11

Across the 13 of 14 papers where every author was matched, so the position is known.

fields
  • cs.IR7
  • cs.LG6
  • cs.CE1
same name
  • Hongzhi Yin — 123 papers, h 79
  • Hongzhi Yin — 57 papers, h 14
  • Hongzhi Yin — 22 papers, h 10
  • Hongzhi Yin — 18 papers, h 11
  • Hongzhi Yin — 6 papers, h 3
  • Hongzhi Yin — 5 papers, h 4

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
20242026
most citedA Survey of Generative Techniques for Spatial-Temporal Data Mining

5 citations · 6 across the 12 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.IR2024

Data Watermarking for Sequential Recommender Systems

Sixiao Zhang, Cheng Long, Wei Yuan +2

In the era of large foundation models, data has become a crucial component in building high-performance AI systems. As the demand for high-quality and large-scale data continues to…

cs.LG2024

HGAurban: Heterogeneous Graph Autoencoding for Urban Spatial-Temporal Learning

Qianru Zhang, Xinyi Gao, Haixin Wang +3

Spatial-temporal graph representations play a crucial role in urban sensing applications, including traffic analysis, human mobility behavior modeling, and citywide crime predictio…

cs.IR2024★ 1 cited

Watermarking Recommender Systems

Sixiao Zhang, Cheng Long, Wei Yuan +2

Recommender systems embody significant commercial value and represent crucial intellectual property. However, the integrity of these systems is constantly challenged by malicious a…

cs.LG2024★ 5 cited

A Survey of Generative Techniques for Spatial-Temporal Data Mining

Qianru Zhang, Haixin Wang, Cheng Long +8

This paper focuses on the integration of generative techniques into spatial-temporal data mining, considering the significant growth and diverse nature of spatial-temporal data. Wi…

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