Lu Qin

207 papers receiving 5.4k citations

Hit Papers

A survey of community search over big graphs 2019 · 207 citations
2070+4+8Years since publication100200300

Peers

Lu Qin
Comparison fields: 5 of 105
  • Signal Processing 2.2k
  • Statistical and Nonlinear Physics 2.1k
  • Computer Networks and Communications 2.4k
  • Computer Vision and Pattern Recognition 1.8k
  • Artificial Intelligence 2.4k
Replace James Cheng with:
James Cheng Hong Kong
Nick Koudas Canada
Jianyong Wang China
Anthony K. H. Tung Singapore
Jianhua Feng China
Aoying Zhou China
Mayur Datar United States
Panos Kalnis Saudi Arabia
Edith Cohen United States
Bolin Ding United States
Lu Qin relative to James Cheng Hong Kong James Cheng's profile →
Citations per field
00.5×1.5×1.8×
James Cheng · 1×
Citations per year

Countries citing papers authored by Lu Qin

Since Specialization
Citations

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

Fields of papers citing papers by Lu Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 220 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Querying k-truss community in large and dynamic graphs
Hit paper breakdown →
2014327
2 2007213
3
A survey of community search over big graphs
Hit paper breakdown →
2019207
4 2016205
5 2015169
6 2008161
7 2017108
8
Keyword Search in Relational Databases: A Survey.
2010101
9 201790
10 201388
11 200987
12 201982
13 201881
14 200979
15 201676
16 201574
17 201274
18 201570
19 202070
20 201869

About Lu Qin

Lu Qin is a scholar working on Signal Processing, Computer Networks and Communications, Artificial Intelligence, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition, having authored 220 papers that have together received 5.5k indexed citations. Recurring topics across this work include Data Management and Algorithms (101 papers), Complex Network Analysis Techniques (79 papers), Graph Theory and Algorithms (62 papers), Advanced Graph Neural Networks (57 papers), Caching and Content Delivery (39 papers), Advanced Database Systems and Queries (35 papers), Advanced Graph Theory Research (31 papers) and Complexity and Algorithms in Graphs (18 papers). The work is most often cited by research in Signal Processing (2.2k citations), Statistical and Nonlinear Physics (2.1k citations), Computer Networks and Communications (2.4k citations), Computer Vision and Pattern Recognition (1.8k citations) and Artificial Intelligence (2.4k citations). Lu Qin has collaborated with scholars based in Australia, China and Hong Kong. Frequent co-authors include Jeffrey Xu Yu, Xuemin Lin, Lijun Chang, Wenjie Zhang, Ying Zhang, Rong-Hua Li, Hong Cheng, Xin Huang, Bolin Ding and Rui Mao. Their work appears in journals such as Proceedings of the VLDB Endowment, The VLDB Journal, IEEE Transactions on Knowledge and Data Engineering, Distributed and Parallel Databases and Nature Communications.

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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