William Wei Song

41 papers receiving 356 citations

Peers

William Wei Song
Comparison fields: 5 of 107
  • Artificial Intelligence 115
  • Information Systems 94
  • Molecular Biology 61
  • Computer Networks and Communications 55
  • Sociology and Political Science 42
Replace Guohui Zhou with:
Guohui Zhou China
Younghoon Kim South Korea
Rizwana Irfan Pakistan
Yi Zhuang China
V. Mahalakshmi India
Yuwen Zhou China
Parul Agarwal India
Song Yang China
Florian Guitton United Kingdom
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William Wei Song relative to Guohui Zhou China Guohui Zhou's profile →
Citations per field
00.5×12.2×
Guohui Zhou · 1×
Citations per year

Countries citing papers authored by William Wei Song

Since Specialization
Citations

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

Fields of papers citing papers by William Wei Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William Wei Song

This figure shows the co-authorship network connecting the top 25 collaborators of William Wei Song. A scholar is included among the top collaborators of William Wei 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 William Wei Song. William Wei 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
#WorkIndexed citations
1 0
2 1
3 0
4 1
5 19
6 2
7 9
8 1
9 13
10 0
11
Collaborative Filtering with Data Classification : A Combined Approach to Hotel Recommendation Systems
2
12 12
13 10
14 11
15 1
16
An Analytic Model of Atomic Service for Services Descriptions.
1
17 1
18 83
19
WDM: A Web Document Model and its Supporting Web Document Analyzer
1
20
An investigation on enterprise modelling integration
1

About William Wei Song

William Wei Song is a scholar working on Information Systems, Computer Networks and Communications and Management Information Systems, having authored 49 papers that have together received 366 indexed citations. Recurring topics across this work include Service-Oriented Architecture and Web Services (15 papers), Semantic Web and Ontologies (7 papers) and Recommender Systems and Techniques (6 papers). The work is most often cited by research in Information Systems (94 citations), Artificial Intelligence (115 citations) and Computer Networks and Communications (55 citations). William Wei Song has collaborated with scholars based in Sweden, China and United Kingdom. Frequent co-authors include Zhenwu Wang, Xiaolin Zheng, Paul F. Williams, Susan V. McLennan, Lisa Lo, Joanne T. M. Tan, Stephen M. Twigg, James Bonner, Yan Wang and Wenyu Zhang. Their work appears in journals such as American Journal of Physiology-Cell Physiology, Information Sciences and Journal of the Association for Information Systems.

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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