Kevin Chen–Chuan Chang

10.6k total citations · 2 hit papers
144 papers, 6.0k citations indexed

About

Kevin Chen–Chuan Chang is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Kevin Chen–Chuan Chang has authored 144 papers receiving a total of 6.0k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Artificial Intelligence, 66 papers in Information Systems and 50 papers in Computer Networks and Communications. Recurrent topics in Kevin Chen–Chuan Chang's work include Web Data Mining and Analysis (42 papers), Data Management and Algorithms (37 papers) and Advanced Database Systems and Queries (37 papers). Kevin Chen–Chuan Chang is often cited by papers focused on Web Data Mining and Analysis (42 papers), Data Management and Algorithms (37 papers) and Advanced Database Systems and Queries (37 papers). Kevin Chen–Chuan Chang collaborates with scholars based in United States, Singapore and China. Kevin Chen–Chuan Chang's co-authors include Vincent W. Zheng, Hongyun Cai, Bin He, Ihab F. Ilyas, Mohamed A. Soliman, Jie Huang, Seung-won Hwang, Chengkai Li, Rui Li and Mitesh Patel and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Communications of the ACM and Computer.

In The Last Decade

Kevin Chen–Chuan Chang

136 papers receiving 5.7k citations

Hit Papers

A Comprehensive Survey of... 2018 2026 2020 2023 2018 2023 400 800 1.2k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kevin Chen–Chuan Chang United States 35 3.4k 2.3k 1.9k 1.4k 1.2k 144 6.0k
Luis Gravano United States 45 3.4k 1.0× 2.9k 1.2× 2.6k 1.3× 2.5k 1.8× 686 0.6× 123 7.2k
Jianyong Wang China 39 3.7k 1.1× 3.3k 1.4× 1.3k 0.7× 1.8k 1.3× 610 0.5× 142 6.2k
Xiaokui Xiao Singapore 53 6.2k 1.9× 1.7k 0.7× 1.7k 0.9× 1.7k 1.2× 1.6k 1.3× 199 9.6k
Hong Cheng Hong Kong 39 3.3k 1.0× 2.6k 1.1× 1.4k 0.8× 1.4k 1.0× 1.8k 1.5× 145 6.3k
Reynold Cheng Hong Kong 40 2.2k 0.7× 1.2k 0.5× 2.1k 1.1× 2.5k 1.8× 922 0.7× 185 5.9k
Aixin Sun Singapore 45 4.9k 1.5× 3.7k 1.6× 836 0.4× 854 0.6× 1.1k 0.8× 223 8.7k
Laks V. S. Lakshmanan Canada 51 3.9k 1.2× 3.3k 1.4× 3.4k 1.8× 2.6k 1.9× 3.3k 2.7× 209 9.1k
Haixun Wang United States 50 6.2k 1.8× 2.7k 1.2× 3.1k 1.6× 3.1k 2.2× 831 0.7× 231 9.6k
Nick Koudas Canada 46 4.2k 1.2× 2.2k 0.9× 4.2k 2.2× 4.2k 3.1× 716 0.6× 187 7.8k
Ming-Syan Chen⋆ Taiwan 44 3.5k 1.0× 4.5k 2.0× 3.6k 1.9× 2.5k 1.8× 435 0.4× 400 10.1k

Countries citing papers authored by Kevin Chen–Chuan Chang

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Chen–Chuan Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin Chen–Chuan Chang. 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 Kevin Chen–Chuan Chang. The network helps show where Kevin Chen–Chuan Chang may publish in the future.

Co-authorship network of co-authors of Kevin Chen–Chuan Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Chen–Chuan Chang. A scholar is included among the top collaborators of Kevin Chen–Chuan Chang 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 Kevin Chen–Chuan Chang. Kevin Chen–Chuan Chang 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
1.
Huang, Jie, et al.. (2023). Expository Text Generation: Imitate, Retrieve, Paraphrase. 11896–11919. 2 indexed citations
2.
Huang, Jie & Kevin Chen–Chuan Chang. (2023). Towards Reasoning in Large Language Models: A Survey. 1049–1065. 195 indexed citations breakdown →
3.
Huang, Jie, Kevin Chen–Chuan Chang, Jinjun Xiong, & Wen‐mei Hwu. (2023). Can Language Models Be Specific? How?. 716–727.
4.
Huang, Jie, et al.. (2023). Descriptive Knowledge Graph in Biomedical Domain. 462–470.
5.
Huang, Jie, et al.. (2022). Coordinated Topic Modeling. 9831–9843.
6.
Huang, Jie, et al.. (2022). Understanding Jargon: Combining Extraction and Generation for Definition Modeling. 3994–4004. 4 indexed citations
7.
Fang, Yuan, Wenqing Lin, Vincent W. Zheng, et al.. (2019). Metagraph-Based Learning on Heterogeneous Graphs. IEEE Transactions on Knowledge and Data Engineering. 33(1). 154–168. 25 indexed citations
8.
Liu, Jixue, Nicole Pratt, Vincent W. Zheng, et al.. (2018). Authenticity and credibility aware detection of adverse drug events from social media. International Journal of Medical Informatics. 120. 157–171. 10 indexed citations
9.
Lin, Miao, Hong Cao, Vincent W. Zheng, Kevin Chen–Chuan Chang, & Shonali Krishnaswamy. (2015). Mobility profiling for user verification with anonymized location data. International Conference on Artificial Intelligence. 960–966. 9 indexed citations
10.
Li, Rui, et al.. (2012). TEDAS: A Twitter-based Event Detection and Analysis System. 1273–1276. 282 indexed citations
11.
Small, Kevin, et al.. (2010). Object Search: Supporting Structured Queries in Web Search Engines. North American Chapter of the Association for Computational Linguistics. 44–52. 2 indexed citations
12.
Chang, Kevin Chen–Chuan, et al.. (2007). Entity search engine: Towards agile best-effort information integration over the Web. Conference on Innovative Data Systems Research. 108–113. 35 indexed citations
13.
Chuang, Shui‐Lung, Kevin Chen–Chuan Chang, & ChengXiang Zhai. (2007). Context-aware wrapping: synchronized data extraction. Very Large Data Bases. 699–710. 28 indexed citations
14.
Cheng, Tao, Xifeng Yan, & Kevin Chen–Chuan Chang. (2007). EntityRank: searching entities directly and holistically. Very Large Data Bases. 387–398. 109 indexed citations
15.
Srivastava, Mani, Jeffrey A Burke, Mark Hansen, et al.. (2006). Network System Challenges in Selective Sharing and Verification for Personal, Social, and Urban-Scale Sensing Applications. eScholarship (California Digital Library). 13 indexed citations
16.
Li, Chengkai, Mohamed A. Soliman, Kevin Chen–Chuan Chang, & Ihab F. Ilyas. (2005). RankSQL: supporting ranking queries in relational database management systems. Very Large Data Bases. 1342–1345. 15 indexed citations
17.
Zhang, Zhen, Bin He, & Kevin Chen–Chuan Chang. (2005). Light-weight domain-based form assistant: querying web databases on the fly. Very Large Data Bases. 97–108. 38 indexed citations
18.
Chang, Kevin Chen–Chuan & Héctor García-Molina. (2000). Approximate Query Translation Across Heterogeneous Information Sources. Very Large Data Bases. 566–577. 18 indexed citations
19.
Li, Wen‐Syan, et al.. (1998). PowerBookmarks: An Advanced Web Bookmark Database System and its Information Sharing and Management.. Kluwer Academic Publishers eBooks. 200–209. 1 indexed citations
20.
Gravano, Luis, Kevin Chen–Chuan Chang, Héctor García-Molina, & Andreas Paepcke. (1997). STARTS: Stanford Proposal for Internet Meta-Searching (Experience Paper).. International Conference on Management of Data. 207–218. 2 indexed citations

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026