Daoguang Zan

461 citations
11 papers · 202 indexed · h-index 6
Topics
Software Engineering Research (5 papers)Topic Modeling (5 papers)Web Data Mining and Analysis (3 papers)
Journals
Knowledge-Based SystemsACM Transactions on Software Engineering and MethodologyProceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

In The Last Decade

Daoguang Zan

11 papers receiving 198 citations

Peers

Daoguang Zan
Comparison fields: 5 of 30
  • Artificial Intelligence 117
  • Information Systems 95
  • Software 66
  • Computer Networks and Communications 22
  • Signal Processing 19
Replace Yuchao Huang with:
Yuchao Huang Canada
Aryaz Eghbali Germany
James Koppel United States
Ming‐Ho Yee Canada
Vijayaraghavan Murali United States
Adrian Lienhard Switzerland
Ensheng Shi China
Tijs van der Storm Netherlands
Quanjun Zhang China
Xujie Si United States
Daoguang Zan relative to Yuchao Huang Canada Yuchao Huang's profile →
Citations per field
00.5×1.5×2.3×
Yuchao Huang · 1×
Citations per year

Countries citing papers authored by Daoguang Zan

Since Specialization
Citations

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

Fields of papers citing papers by Daoguang Zan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daoguang Zan

This figure shows the co-authorship network connecting the top 25 collaborators of Daoguang Zan. A scholar is included among the top collaborators of Daoguang Zan 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 Daoguang Zan. Daoguang Zan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
#WorkIndexed citations
1 1
2 1
3 4
4 1
5 6
6 59
7 1
8 53
9 20
10 37
11 19

About Daoguang Zan

Daoguang Zan is a scholar working on Software, Information Systems and Artificial Intelligence, having authored 11 papers that have together received 202 indexed citations. Recurring topics across this work include Software Engineering Research (5 papers), Topic Modeling (5 papers) and Web Data Mining and Analysis (3 papers). The work is most often cited by research in Software (66 citations), Information Systems (95 citations) and Health Informatics (5 citations). Daoguang Zan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Jian–Guang Lou, Weizhu Chen, Bei Chen, Bei Guan, Yongji Wang, Bingchao Wu, Dianjie Lu, Yongji Wang, Zeqi Lin and Jacky Keung. Their work appears in journals such as Knowledge-Based Systems, ACM Transactions on Software Engineering and Methodology and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.

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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