Zhumin Chen

5.2k total citations · 1 hit paper
97 papers, 2.9k citations indexed

About

Zhumin Chen is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zhumin Chen has authored 97 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Artificial Intelligence, 44 papers in Information Systems and 13 papers in Computer Vision and Pattern Recognition. Recurrent topics in Zhumin Chen's work include Topic Modeling (42 papers), Recommender Systems and Techniques (29 papers) and Natural Language Processing Techniques (27 papers). Zhumin Chen is often cited by papers focused on Topic Modeling (42 papers), Recommender Systems and Techniques (29 papers) and Natural Language Processing Techniques (27 papers). Zhumin Chen collaborates with scholars based in China, Netherlands and United States. Zhumin Chen's co-authors include Pengjie Ren, Jun Ma, Zhaochun Ren, Maarten de Rijke, Tao Lian, Jing Li, Jun Ma, Shuai Gao, Furu Wei and Guanghui Wang and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, Physica A Statistical Mechanics and its Applications and Computers & Mathematics with Applications.

In The Last Decade

Zhumin Chen

90 papers receiving 2.8k 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.

Neural Attentive Session-based Recommendation

2017 851 citations Pengjie Ren, Zhumin Chen et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Zhumin Chen China	26	2.0k	1.8k	460	456	304	97	2.9k
Zhaochun Ren China	33	3.1k 1.5×	2.2k 1.2×	731 1.6×	455 1.0×	195 0.6×	147	3.9k
Pablo Castells Spain	29	1.5k 0.7×	2.3k 1.3×	534 1.2×	741 1.6×	132 0.4×	115	3.0k
Ana-Maria Popescu United States	16	3.3k 1.6×	1.3k 0.8×	273 0.6×	322 0.7×	337 1.1×	32	3.9k
Xiaoyuan Su United States	10	1.0k 0.5×	2.1k 1.2×	736 1.6×	324 0.7×	152 0.5×	22	2.6k
Alexandrin Popescul United States	13	782 0.4×	1.1k 0.6×	373 0.8×	238 0.5×	280 0.9×	19	1.6k
Abraham Gutiérrez Spain	11	1.0k 0.5×	2.0k 1.1×	695 1.5×	374 0.8×	141 0.5×	41	2.5k
Yao Wu China	17	792 0.4×	830 0.5×	315 0.7×	391 0.9×	252 0.8×	42	1.6k
Panagiotis Symeonidis Greece	23	853 0.4×	1.1k 0.6×	344 0.7×	160 0.4×	376 1.2×	68	1.8k
Rosie Jones United States	26	1.8k 0.9×	1.7k 1.0×	331 0.7×	243 0.5×	144 0.5×	62	3.1k

Countries citing papers authored by Zhumin Chen

Since Specialization

Citations

This map shows the geographic impact of Zhumin Chen'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 Zhumin Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhumin Chen more than expected).

Fields of papers citing papers by Zhumin Chen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhumin Chen. 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 Zhumin Chen. The network helps show where Zhumin Chen may publish in the future.

Co-authorship network of co-authors of Zhumin Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Zhumin Chen. A scholar is included among the top collaborators of Zhumin Chen 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 Zhumin Chen. Zhumin Chen 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.

Xie, Ruobing, et al.. (2025). Exploration and Exploitation of Hard Negative Samples for Cross-Domain Sequential Recommendation. 669–677.

2.

Chen, Zhumin, et al.. (2025). Towards real-time and robust lane detection: a DCN–EMCAM empowered UFLD model. Engineering Research Express. 7(2). 25295–25295. 1 indexed citations

3.

Ren, Pengjie, et al.. (2024). MELoRA: Mini-Ensemble Low-Rank Adapters for Parameter-Efficient Fine-Tuning. VU Research Portal. 3052–3064. 2 indexed citations

4.

Zhang, Mengqi, et al.. (2024). Self-Supervised Position Debiasing for Large Language Models. 2897–2917.

5.

Gao, Shen, et al.. (2024). Generative News Recommendation. Leiden Repository (Leiden University). 3444–3453. 12 indexed citations

6.

Ren, Zhaochun, Ruobing Xie, Yan Su, et al.. (2024). Content-Based Collaborative Generation for Recommender Systems. Leiden Repository (Leiden University). 2420–2430. 2 indexed citations

7.

Zhang, Shuo, Weiwei Sun, Shen Gao, et al.. (2024). Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering. Leiden Repository (Leiden University). 7339–7353. 4 indexed citations

8.

Wang, Shuaiqiang, Dawei Yin, Pengjie Ren, et al.. (2024). KnowTuning: Knowledge-aware Fine-tuning for Large Language Models. Leiden Repository (Leiden University). 14535–14556. 2 indexed citations

9.

Chen, Zhumin, et al.. (2023). Center-retained fine-tuning for conversational question ranking through unsupervised center identification. Information Processing & Management. 61(2). 103578–103578. 1 indexed citations

10.

Ren, Pengjie, Zhumin Chen, Zhaochun Ren, et al.. (2022). Mixed Information Flow for Cross-Domain Sequential Recommendations. ACM Transactions on Knowledge Discovery from Data. 16(4). 1–32. 32 indexed citations

11.

Ren, Pengjie, et al.. (2022). Improving Transformer-based Sequential Recommenders through Preference Editing. ACM Transactions on Information Systems. 41(3). 1–24. 15 indexed citations

12.

Wang, Shanshan, Pengjie Ren, Zhumin Chen, et al.. (2020). Coding Electronic Health Records with Adversarial Reinforcement Path Generation. UvA-DARE (University of Amsterdam). 801–810. 11 indexed citations

13.

Ren, Pengjie, Furu Wei, Zhumin Chen, Jun Ma, & Ming Zhou. (2016). A Redundancy-Aware Sentence Regression Framework for Extractive Summarization. International Conference on Computational Linguistics. 33–43. 31 indexed citations

14.

Ma, Jun, et al.. (2014). Ranking the spreading ability of nodes in complex networks based on local structure. Physica A Statistical Mechanics and its Applications. 403. 130–147. 154 indexed citations

15.

Wang, Guanghui, Zhumin Chen, & Jihui Wang. (2014). Neighbor sum distinguishing index of planar graphs. Discrete Mathematics. 334. 70–73. 22 indexed citations

16.

Gao, Shuai, Jun Ma, & Zhumin Chen. (2014). Effective and effortless features for popularity prediction in microblogging network. 269–270. 32 indexed citations

17.

Chen, Zhumin. (2009). A Heuristic Algorithm for Hybrid Flow Shop's Master Scheduling. Industrial Engineering and Management. 2 indexed citations

18.

Chen, Zhumin, Jun Ma, Xiaohui Han, & Dongmei Zhang. (2008). An effective relevance prediction algorithm based on hierarchical taxonomy for focused crawling. 613–619. 3 indexed citations

19.

Chen, Zhumin. (2008). Genetic Algorithms for Multi-objective Optimization of Operation Sequencing. Mechanical Engineer. 4 indexed citations

20.

Chen, Zhumin. (2007). Improved Shark-Search algorithm based on page segmentation. Journal of Shandong University.

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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