Z. J. Chen

462 total citations
5 papers, 10 citations indexed

About

Z. J. Chen is a scholar working on Information Systems, Computational Theory and Mathematics and Information Systems and Management. According to data from OpenAlex, Z. J. Chen has authored 5 papers receiving a total of 10 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Information Systems, 2 papers in Computational Theory and Mathematics and 1 paper in Information Systems and Management. Recurrent topics in Z. J. Chen's work include Recommender Systems and Techniques (3 papers), Advanced Multi-Objective Optimization Algorithms (2 papers) and Text and Document Classification Technologies (1 paper). Z. J. Chen is often cited by papers focused on Recommender Systems and Techniques (3 papers), Advanced Multi-Objective Optimization Algorithms (2 papers) and Text and Document Classification Technologies (1 paper). Z. J. Chen collaborates with scholars based in China and United States. Z. J. Chen's co-authors include Hongke Zhao, Ding-Bang Luh, Lei Zhang, Likang Wu and Mengyun Ke and has published in prestigious journals such as Information Sciences, Microorganisms and IEEE Transactions on Big Data.

In The Last Decade

Z. J. Chen

3 papers receiving 10 citations

Peers

Z. J. Chen
Angela Robinson United States
P. Wilson United Kingdom
Nick Ryder Germany
Duligur Ibeling United States
Sergei V Gleyzer United States
Bram Wasti United States
Angela Robinson United States
Z. J. Chen
Citations per year, relative to Z. J. Chen Z. J. Chen (= 1×) peers Angela Robinson

Countries citing papers authored by Z. J. Chen

Since Specialization
Citations

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

Fields of papers citing papers by Z. J. Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Z. J. Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Z. J. Chen. A scholar is included among the top collaborators of Z. J. 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 Z. J. Chen. Z. J. Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

5 of 5 papers shown
2.
Zhang, Lei, et al.. (2025). Multi-Objective Graph Contrastive Learning for Recommendation. IEEE Transactions on Big Data. 11(5). 2696–2709.
3.
Zhang, Lei, et al.. (2024). MOREM: An evolutionary multitasking optimization algorithm for multi-objective recommendations. Information Sciences. 678. 120921–120921. 1 indexed citations
4.
Luh, Ding-Bang, et al.. (2024). A Systematic Review and Meta-Analysis of Eye-Tracking Studies for Consumers’ Visual Attention in Online Shopping. Information Technology And Control. 53(1). 187–205. 2 indexed citations
5.
Zhang, Lei, et al.. (2024). A Multi-Population Based Evolutionary Algorithm for Many-Objective Recommendations. IEEE Transactions on Emerging Topics in Computational Intelligence. 8(2). 1969–1982. 7 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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