Xiangmin Zhou

3.0k total citations · 1 hit paper
114 papers, 2.1k citations indexed

About

Xiangmin Zhou is a scholar working on Numerical Analysis, Computer Vision and Pattern Recognition and Computational Mechanics. According to data from OpenAlex, Xiangmin Zhou has authored 114 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Numerical Analysis, 29 papers in Computer Vision and Pattern Recognition and 27 papers in Computational Mechanics. Recurrent topics in Xiangmin Zhou's work include Numerical methods for differential equations (29 papers), Video Analysis and Summarization (18 papers) and Recommender Systems and Techniques (18 papers). Xiangmin Zhou is often cited by papers focused on Numerical methods for differential equations (29 papers), Video Analysis and Summarization (18 papers) and Recommender Systems and Techniques (18 papers). Xiangmin Zhou collaborates with scholars based in Australia, United States and China. Xiangmin Zhou's co-authors include Kumar K. Tamma, Lei Chen, D. Sha, Athman Bouguettaya, Qi Yu, Xumin Liu, Andy Song, Xiaofang Zhou, Siti Ujila Masuri and Yanchun Zhang and has published in prestigious journals such as The Journal of Urology, Expert Systems with Applications and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

Xiangmin Zhou

102 papers receiving 2.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Efficient agglomerative hierarchical clustering

2014 301 citations Xiangmin Zhou et al. Expert Systems with Applications profile →

Peers

Xiangmin Zhou

NA

CM

AI

CVPR

SNP

Junaid Ali Khan Pakistan

Jon Lee United States

Muhammad Sulaiman Pakistan

Adil Bagirov Australia

Zaer S. Abo‐Hammour Jordan

Jaroslaw Sobieszczanski‐Sobieski United States

Frédéric Magoulès France

Sohrab Effati Iran

Abd Allah A. Mousa Saudi Arabia

Vasilios N. Katsikis Greece

Junaid Ali Khan Pakistan

Xiangmin Zhou

205 ×0.3

NA

189 ×0.4

CM

376 ×0.9

AI

237 ×0.7

CVPR

276 ×0.8

SNP

Citations per year, relative to Xiangmin Zhou Xiangmin Zhou (= 1×) peers Junaid Ali Khan

Countries citing papers authored by Xiangmin Zhou

Since Specialization

Citations

This map shows the geographic impact of Xiangmin Zhou's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiangmin Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiangmin Zhou more than expected).

Fields of papers citing papers by Xiangmin Zhou

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiangmin Zhou. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiangmin Zhou. The network helps show where Xiangmin Zhou may publish in the future.

Co-authorship network of co-authors of Xiangmin Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Xiangmin Zhou. A scholar is included among the top collaborators of Xiangmin Zhou based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiangmin Zhou. Xiangmin Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Zhou, Xiangmin, Lei Chen, Chengkun He, et al.. (2025). A Responsible and Extendable Context-Aware Recommender System. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 2955–2958.

2.

Ali, Waqar, Muhammad Ammad-ud-din, Xiangmin Zhou, Yan Zhang, & Jie Shao. (2024). Communication-Efficient Federated Neural Collaborative Filtering with Multi-Armed Bandits. 4(1). 1–28. 5 indexed citations

3.

He, Chengkun, et al.. (2024). Online Anomaly Detection over Live Social Video Streaming. 4760–4772.

4.

Cheng, Yurong, Xiaosong Huang, Yi Yang, et al.. (2024). Cross Online Ride-Sharing for Multiple-Platform Cooperations in Spatial Crowdsourcing. 4140–4152. 2 indexed citations

5.

Ali, Waqar, Xiangmin Zhou, & Jie Shao. (2024). Privacy-preserved and Responsible Recommenders: From Conventional Defense to Federated Learning and Blockchain. ACM Computing Surveys. 57(5). 1–35. 7 indexed citations

6.

Shen, Derong, Xiangmin Zhou, Yue Kou, et al.. (2024). Enhancing Deep Entity Resolution with Integrated Blocker-Matcher Training: Balancing Consensus and Discrepancy. 508–518.

7.

Wang, Yansong, Hui Xu, Waqar Ali, Xiangmin Zhou, & Jie Shao. (2024). Bilateral Improvement in Local Personalization and Global Generalization in Federated Learning. IEEE Internet of Things Journal. 11(16). 27099–27111.

8.

Ali, Waqar, Khalid Umer, Xiangmin Zhou, & Jie Shao. (2024). HidAttack: An Effective and Undetectable Model Poisoning Attack to Federated Recommenders. IEEE Transactions on Knowledge and Data Engineering. 37(3). 1227–1240. 1 indexed citations

9.

Yang, Xiaochun, et al.. (2024). Adaptive Intention Learning for Session-Based Recommendation. ACM Transactions on Intelligent Systems and Technology. 16(2). 1–26. 1 indexed citations

10.

Shen, Derong, et al.. (2023). Soft Target-Enhanced Matching Framework for Deep Entity Matching. Proceedings of the AAAI Conference on Artificial Intelligence. 37(4). 4259–4266. 4 indexed citations

11.

Ali, Waqar, Rajesh Kumar, Xiangmin Zhou, & Jie Shao. (2023). Responsible Recommendation Services with Blockchain Empowered Asynchronous Federated Learning. ACM Transactions on Intelligent Systems and Technology. 15(4). 1–24. 7 indexed citations

12.

Wang, Yansong, et al.. (2023). FedFTHA: A Fine-Tuning and Head Aggregation Method in Federated Learning. IEEE Internet of Things Journal. 10(14). 12749–12762. 14 indexed citations

13.

Zhou, Xiangmin, et al.. (2023). Dynamic Bi-layer Graph Learning for Context-aware Sequential Recommendation. 2(2). 1–23. 3 indexed citations

14.

Zhou, Xiangmin, et al.. (2022). Complex Event Summarization Using Multi-Social Attribute Correlation. IEEE Transactions on Knowledge and Data Engineering. 35(11). 11180–11195. 3 indexed citations

15.

Chen, Xi, Xiangmin Zhou, Jeffrey Chan, et al.. (2020). Event Popularity Prediction Using Influential Hashtags From Social Media. IEEE Transactions on Knowledge and Data Engineering. 34(10). 4797–4811. 11 indexed citations

16.

Zhou, Xiangmin, et al.. (2018). Dynamic Connection-Based Social Group Recommendation. IEEE Transactions on Knowledge and Data Engineering. 32(3). 453–467. 44 indexed citations

17.

Chen, Xi, Xiangmin Zhou, Timos Sellis, & Xue Li. (2018). Social event detection with retweeting behavior correlation. Expert Systems with Applications. 114. 516–523. 28 indexed citations

18.

Zhou, Xiangmin, Lei Chen, Yanchun Zhang, et al.. (2017). Enhancing online video recommendation using social user interactions. The VLDB Journal. 26(5). 637–656. 26 indexed citations

19.

Georgakopoulos, Dimitrios, Rajiv Ranjan, Karan Mitra, & Xiangmin Zhou. (2012). MediaWise - Designing a Smart Media Cloud. Swinburne Research Bank (Swinburne University of Technology). 2 indexed citations

20.

Shen, Heng Tao, Xiaofang Zhou, Zi Huang, Jie Shao, & Xiangmin Zhou. (2007). UQLIPS: a real-time near-duplicate video clip detection system. Queensland's institutional digital repository (The University of Queensland). 1374–1377. 59 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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