Luobing Dong

410 citations
17 papers · 259 · h-index 8

Impact in

Papers in

Luobing Dong

16 papers receiving 254 citations

Peers

Luobing Dong
Comparison fields: 5 of 63
  • Computer Networks and Communications 149
  • Information Systems 80
  • Business and International Management 6
  • Computer Vision and Pattern Recognition 54
  • Artificial Intelligence 66
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Pritam Gajkumar Shah India
Eunmok Yang South Korea
U. Venkanna India
Qusay Idrees Sarhan Iraq
Ali Alnoman Canada
Zhuoqing Chang China
Subhranshu Sekhar Tripathy India
Kennedy Chinedu Okafor Nigeria
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Citations per year

Countries citing papers authored by Luobing Dong

Since Specialization
Citations

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

Fields of papers citing papers by Luobing Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 201969
2 201831
3 201927
4 202126
5 202224
6 202021
7 202220
8 202012
9 20237
10 20187
11 20156
12
Research on a Compound Keywords Detection Method Based on Small World Model
20093
13 19943
14
QoS Optimal Location-Based Services Architecture Based on Mobile Cloud Computing and Behavior Prediction
20151
15 20221
16 20201
17 20250

About Luobing Dong

Luobing Dong is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 17 papers that have together received 259 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (5 papers), Natural Language Processing Techniques (3 papers), Vehicular Ad Hoc Networks (VANETs) (2 papers), Advanced Text Analysis Techniques (2 papers), Topic Modeling (2 papers), Wireless Communication Networks Research (1 paper), Green IT and Sustainability (1 paper) and Color perception and design (1 paper). The work is most often cited by research in Computer Networks and Communications (149 citations), Information Systems (80 citations), Business and International Management (6 citations), Computer Vision and Pattern Recognition (54 citations) and Artificial Intelligence (66 citations). Luobing Dong has collaborated with scholars based in China, United States and Portugal. Frequent co-authors include Weili Wu, Ding Zhu Du, Taieb Znati, Ding‐Zhu Du, Baoqi Liu, Xing Wang, Chuanhe Huang, Honghao Gao, Qiufen Ni and Yanfei Liu. Their work appears in journals such as Theoretical Computer Science, IEEE Transactions on Computational Social Systems, IEEE Internet of Things Journal, IEEE Transactions on Reliability and Light Science & 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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