Shaoxu Song

2.2k citations
111 papers · 1.5k · h-index 22

Impact in

Papers in

Shaoxu Song

98 papers receiving 1.5k citations

Peers

Shaoxu Song
Comparison fields: 5 of 90
  • Management Science and Operations Research 595
  • Signal Processing 501
  • Artificial Intelligence 778
  • Computer Networks and Communications 486
  • Information Systems 459
Replace Shawn R. Jeffery with:
Shawn R. Jeffery United States
Dmitri V. Kalashnikov United States
Benjamin Moseley United States
G. Sahoo India
William H. Sanders United States
Anastasios Gounaris Greece
H. Kargupta United States
Paulo Costa United States
Chris Olston United States
Antonios Deligiannakis Greece
Shaoxu Song relative to Shawn R. Jeffery United States Shawn R. Jeffery's profile →
Citations per field
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Citations per year

Countries citing papers authored by Shaoxu Song

Since Specialization
Citations

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

Fields of papers citing papers by Shaoxu Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 111 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201799
2 201189
3 201574
4 201668
5 201553
6 201850
7 201649
8 201544
9 201341
10 201541
11 200938
12 202336
13 201435
14 201935
15 201335
16 201632
17 201531
18 201027
19 202027
20 201625

About Shaoxu Song

Shaoxu Song is a scholar working on Artificial Intelligence, Management Science and Operations Research, Signal Processing, Computer Networks and Communications and Information Systems, having authored 111 papers that have together received 1.5k indexed citations. Recurring topics across this work include Data Quality and Management (51 papers), Advanced Database Systems and Queries (36 papers), Data Management and Algorithms (27 papers), Time Series Analysis and Forecasting (24 papers), Data Mining Algorithms and Applications (16 papers), Anomaly Detection Techniques and Applications (13 papers), Semantic Web and Ontologies (12 papers) and Privacy-Preserving Technologies in Data (8 papers). The work is most often cited by research in Management Science and Operations Research (595 citations), Signal Processing (501 citations), Artificial Intelligence (778 citations), Computer Networks and Communications (486 citations) and Information Systems (459 citations). Shaoxu Song has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Lei Chen, Jianmin Wang, Aoqian Zhang, Philip S. Yu, Lei Zou, Jeffrey Xu Yu, Hong Cheng, Xuemin Lin, Yu Sun and Xiang Lian. Their work appears in journals such as Proceedings of the VLDB Endowment, IEEE Transactions on Knowledge and Data Engineering, The VLDB Journal, ACM Transactions on Database Systems and Ultrasonics Sonochemistry.

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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