Cheng Long

3.2k citations
172 papers · 1.9k indexed · h-index 24

Impact in

    • Data Management and Algorithms
    • Time Series Analysis and Forecasting
    • Human Mobility and Location-Based Analysis

Papers in

Cheng Long

155 papers receiving 1.9k citations

Peers

Cheng Long
Comparison fields: 5 of 138
  • Signal Processing 616
  • Transportation 248
  • Geography, Planning and Development 195
  • Artificial Intelligence 594
  • Computer Vision and Pattern Recognition 327
Replace Xiaoru Yuan with:
Xiaoru Yuan China
Ickjai Lee Australia
Rui Zhou China
Jae-Gil Lee South Korea
Seth Rogers United States
Stefan Wrobel Germany
Raymond Chi-Wing Wong Hong Kong
Donato Malerba Italy
Bo Han China
Cheng Long relative to Xiaoru Yuan China Xiaoru Yuan's profile →
Citations per field
00.5×2.9×
Xiaoru Yuan · 1×
Citations per year

Countries citing papers authored by Cheng Long

Since Specialization
Citations

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

Fields of papers citing papers by Cheng Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Cheng Long, 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 Cheng Long Line = papers co-authored together Cheng Long links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 172 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201382
2 202177
3 201374
4 201968
5 202154
6 201854
7 202051
8 202051
9 201149
10 202049
11 201448
12 201444
13 202141
14 201339
15 202038
16 202031
17 201431
18 201929
19 201827
20 201827

About Cheng Long

Cheng Long is a scholar working on Signal Processing, Transportation, Geography, Planning and Development, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 172 papers that have together received 1.9k indexed citations. Recurring topics across this work include Data Management and Algorithms (48 papers), Human Mobility and Location-Based Analysis (14 papers), Advanced Database Systems and Queries (13 papers), Traffic Prediction and Management Techniques (13 papers), Geographic Information Systems Studies (12 papers), Advanced Image and Video Retrieval Techniques (12 papers), Data Mining Algorithms and Applications (11 papers) and Complex Network Analysis Techniques (11 papers). The work is most often cited by research in Signal Processing (616 citations), Transportation (248 citations), Geography, Planning and Development (195 citations), Artificial Intelligence (594 citations) and Computer Vision and Pattern Recognition (327 citations). Cheng Long has collaborated with scholars based in Singapore, China and Hong Kong. Frequent co-authors include Raymond Chi-Wing Wong, Gao Cong, H. V. Jagadish, Huiyu Zhou, Pan Xiong, Zheng Wang, Xuemin Zhang, Ada Wai-Chee Fu, Ke Wang and Jianyang Gao. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Proceedings of the VLDB Endowment, ACM Transactions on Knowledge Discovery from Data, ACM Transactions on Database Systems and Sustainability.

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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