Chien-Chung Chan

2.0k total citations
42 papers, 641 citations indexed

About

Chien-Chung Chan is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Information Systems. According to data from OpenAlex, Chien-Chung Chan has authored 42 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computational Theory and Mathematics, 19 papers in Artificial Intelligence and 17 papers in Information Systems. Recurrent topics in Chien-Chung Chan's work include Rough Sets and Fuzzy Logic (20 papers), Data Mining Algorithms and Applications (14 papers) and Fuzzy Logic and Control Systems (7 papers). Chien-Chung Chan is often cited by papers focused on Rough Sets and Fuzzy Logic (20 papers), Data Mining Algorithms and Applications (14 papers) and Fuzzy Logic and Control Systems (7 papers). Chien-Chung Chan collaborates with scholars based in United States, Taiwan and Canada. Chien-Chung Chan's co-authors include Wojciech Ziarko, Jerzy W. Grzymala‐Busse, Natheer Khasawneh, C. Batur, Celal Batur, Shengyong Wang, Zhong-Hui Duan, A. Srinivasan, Federico de Gregorio and Gwo‐Hshiung Tzeng and has published in prestigious journals such as Information Sciences, The International Journal of Advanced Manufacturing Technology and Engineering Applications of Artificial Intelligence.

In The Last Decade

Chien-Chung Chan

38 papers receiving 581 citations

Peers

Chien-Chung Chan
John Shafer United States
Chid Apte United States
Se June Hong United States
Chien-Chung Chan
Citations per year, relative to Chien-Chung Chan Chien-Chung Chan (= 1×) peers Cheng‐Jung Tsai

Countries citing papers authored by Chien-Chung Chan

Since Specialization
Citations

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

Fields of papers citing papers by Chien-Chung Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chien-Chung Chan. 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 Chien-Chung Chan. The network helps show where Chien-Chung Chan may publish in the future.

Co-authorship network of co-authors of Chien-Chung Chan

This figure shows the co-authorship network connecting the top 25 collaborators of Chien-Chung Chan. A scholar is included among the top collaborators of Chien-Chung Chan 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 Chien-Chung Chan. Chien-Chung Chan 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.
Nguyen, Hoang, et al.. (2016). RedTweet: recommendation engine for reddit. Journal of Intelligent Information Systems. 47(2). 247–265. 6 indexed citations
2.
Nguyen, Hoang, et al.. (2015). RedTweet. 1381–1388. 4 indexed citations
3.
Chan, Chien-Chung, et al.. (2015). Recommenddit: A Recommendation Service for Reddit Communities. 374–379. 1 indexed citations
4.
Peters, James F., Wojciech Ziarko, Jerzy W. Grzymala‐Busse, Chien-Chung Chan, & Andrzej Skowron. (2011). Transactions on Rough Sets XIII. Lecture notes in computer science. 15 indexed citations
5.
Chan, Chien-Chung, et al.. (2010). User Centred Design for Self-Service Point in MTR. 1 indexed citations
6.
Chan, Chien-Chung & Gwo‐Hshiung Tzeng. (2009). Representation of second-order Dominance-based approximation space by neighborhood systems. 4062. 33–38.
7.
Chan, Chien-Chung & Gwo‐Hshiung Tzeng. (2009). Dominance-Based Rough Sets Using Indexed Blocks as Granules. Fundamenta Informaticae. 94(2). 133–146. 3 indexed citations
8.
Chan, Chien-Chung, et al.. (2008). Protein function prediction using decision trees. 31. 193–199. 1 indexed citations
9.
Chan, Chien-Chung, et al.. (2008). Improve neuro-fuzzy learning by attribute reduction. 27. 1–5. 2 indexed citations
10.
Chan, Chien-Chung & Shusaku Tsumoto. (2007). On Learning Decision Rules From Flow Graphs. 655–658. 1 indexed citations
11.
Chan, Chien-Chung. (2007). A Framework for Assessing Usage of Web-Based e-Learning Systems. 147–147. 7 indexed citations
12.
Khasawneh, Natheer & Chien-Chung Chan. (2007). Multidimensional Sessions Comparison Method Using Dynamic Programming. 10. 581–585. 2 indexed citations
13.
Khasawneh, Natheer & Chien-Chung Chan. (2005). Web Usage Mining Using Rough Sets. 580–585. 10 indexed citations
14.
Chan, Chien-Chung, et al.. (2003). Rule-Based Classifier for Bankruptcy Protection.. 74–81. 2 indexed citations
15.
Xu, Tianhe, Yu‐Jiun Lin, & Chien-Chung Chan. (2003). A Web-Based Product Modelling Tool ? A Preliminary Development. The International Journal of Advanced Manufacturing Technology. 21(9). 669–677. 7 indexed citations
16.
Batur, C., A. Srinivasan, & Chien-Chung Chan. (2002). Automated rule based model generation for uncertain complex dynamic systems. 275–279. 4 indexed citations
17.
Chan, Chien-Chung. (1998). A rough set approach to attribute generalization in data mining. Information Sciences. 107(1-4). 169–176. 138 indexed citations
18.
Batur, Celal, et al.. (1993). Inverse Fuzzy Model Controllers. 772–776. 10 indexed citations
19.
Batur, Celal, et al.. (1993). Using inductive learning to determine fuzzy rules for dynamic systems. Engineering Applications of Artificial Intelligence. 6(3). 257–264. 8 indexed citations
20.
Chan, Chien-Chung. (1989). Learning rules from examples under uncertainty--an approach based on rough-set boundaries and entropy.

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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