Shaoxu Song

2.1k total citations
112 papers, 1.3k citations indexed

About

Shaoxu Song is a scholar working on Artificial Intelligence, Management Science and Operations Research and Signal Processing. According to data from OpenAlex, Shaoxu Song has authored 112 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Artificial Intelligence, 51 papers in Management Science and Operations Research and 43 papers in Signal Processing. Recurrent topics in Shaoxu Song's work include Data Quality and Management (50 papers), Advanced Database Systems and Queries (36 papers) and Data Management and Algorithms (24 papers). Shaoxu Song is often cited by papers focused on Data Quality and Management (50 papers), Advanced Database Systems and Queries (36 papers) and Data Management and Algorithms (24 papers). Shaoxu Song collaborates with scholars based in China, Hong Kong and United States. Shaoxu Song's co-authors include Lei Chen, Jianmin Wang, Aoqian Zhang, Philip S. Yu, Yu Sun, Jeffrey Xu Yu, Hong Cheng, Xuemin Lin, Lei Zou and Xiang Lian and has published in prestigious journals such as Information Sciences, Journal of Physics D Applied Physics and Journal of Alloys and Compounds.

In The Last Decade

Shaoxu Song

97 papers receiving 1.3k citations

Peers

Shaoxu Song
Comparison fields: 5 of 86
  • Artificial Intelligence 680
  • Management Science and Operations Research 520
  • Signal Processing 449
  • Computer Networks and Communications 439
  • Information Systems 376
Replace Jianling Sun with:
Jianling Sun China
Qingwei Lin China
Antonios Deligiannakis Greece
D. Yang China
P. Dhavachelvan India
Habiba Drias Algeria
Odej Kao Germany
Guiyi Wei China
Sven Hartmann Germany
H. Kargupta United States
Jianling Sun China View profile →
Citations per field, relative to Shaoxu Song
Shaoxu Song · 1×
Citations per year, relative to Shaoxu Song
Shaoxu Song · 1×

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-authorship network of co-authors of Shaoxu Song

This figure shows the co-authorship network connecting the top 25 collaborators of Shaoxu Song. A scholar is included among the top collaborators of Shaoxu Song based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shaoxu Song. Shaoxu Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 1
3 1
4 0
5 1
6 1
7 0
8 0
9 0
10 1
11 6
12 1
13 0
14 15
15 4
16 7
17 45
18 15
19 15
20
TCUAP: A Novel Approach of Text Clustering Using Asymmetric Proximity.
2

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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