Jun Ma

5.2k citations
120 papers · 3.5k · 1 hit paper · h-index 29

Impact in

Papers in

    • Recommender Systems and Techniques 35
    • Web Data Mining and Analysis 16
    • Topic Modeling 13
    • Advanced Graph Neural Networks 12
    • Text and Document Classification Technologies 11

Jun Ma

112 papers receiving 3.4k citations

Jun Ma's Hit Papers

Neural Attentive Session-based Recommendation 2017 · 981 citations
9810+3+6Years since publication250500750

Peers

Jun Ma
Comparison fields: 5 of 122
  • Information Systems 2.2k
  • Artificial Intelligence 2.1k
  • Computer Vision and Pattern Recognition 1.0k
  • Management Science and Operations Research 531
  • Health Information Management 95
Replace Kenji Yamanishi with:
Kenji Yamanishi Japan
Thomas Lukasiewicz United Kingdom
Jason D. M. Rennie United States
Haifeng Liu China
Margaret H. Dunham United States
Giorgio Terracina Italy
Xianghan Zheng China
Rong Jin United States
Jun Ma relative to Kenji Yamanishi Japan Kenji Yamanishi's profile →
Citations per field
00.5×5.0×
Kenji Yamanishi · 1×
Citations per year

Countries citing papers authored by Jun Ma

Since Specialization
Citations

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

Fields of papers citing papers by Jun Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Ma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun Ma Line = papers co-authored together Jun Ma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 120 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Neural Attentive Session-based Recommendation
Hit paper breakdown →
2017981
2 2019192
3 2019185
4 2021137
5 2017137
6 2019111
7 2017100
8 201997
9 201987
10 202086
11 201784
12 201977
13 202067
14 201760
15 201954
16 201944
17 201643
18 201841
19 202040
20 201839

About Jun Ma

Jun Ma is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 120 papers that have together received 3.5k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (35 papers), Image Retrieval and Classification Techniques (17 papers), Advanced Image and Video Retrieval Techniques (16 papers), Web Data Mining and Analysis (16 papers), Topic Modeling (13 papers), Advanced Graph Neural Networks (12 papers), Text and Document Classification Technologies (11 papers) and Caching and Content Delivery (11 papers). The work is most often cited by research in Information Systems (2.2k citations), Artificial Intelligence (2.1k citations), Computer Vision and Pattern Recognition (1.0k citations), Management Science and Operations Research (531 citations) and Health Information Management (95 citations). Jun Ma has collaborated with scholars based in China, Netherlands and United States. Frequent co-authors include Zhumin Chen, Pengjie Ren, Zhaochun Ren, Maarten de Rijke, Tao Lian, Jing Li, Imran Qureshi, Qaisar Abbas, Shuaiqiang Wang and Liqiang Nie. Their work appears in journals such as ACM Transactions on Information Systems, Soft Computing, ACM Transactions on Intelligent Systems and Technology, IEEE Transactions on Knowledge and Data Engineering and Expert Systems with Applications.

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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