Ching-Seh Wu

494 total citations
24 papers, 299 citations indexed

About

Ching-Seh Wu is a scholar working on Information Systems, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Ching-Seh Wu has authored 24 papers receiving a total of 299 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Information Systems, 12 papers in Computer Networks and Communications and 9 papers in Artificial Intelligence. Recurrent topics in Ching-Seh Wu's work include Service-Oriented Architecture and Web Services (8 papers), Software Engineering Research (4 papers) and Software System Performance and Reliability (4 papers). Ching-Seh Wu is often cited by papers focused on Service-Oriented Architecture and Web Services (8 papers), Software Engineering Research (4 papers) and Software System Performance and Reliability (4 papers). Ching-Seh Wu collaborates with scholars based in United States and Taiwan. Ching-Seh Wu's co-authors include Wei‐Chun Chang, Katerina Potika, Chun‐Yen Chang, Ishwar K. Sethi, Melody Moh, Wendy Lee, Teng-Sheng Moh and David Taylor and has published in prestigious journals such as INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences and IEEE Transactions on Information Technology in Biomedicine.

In The Last Decade

Ching-Seh Wu

23 papers receiving 274 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ching-Seh Wu United States 10 156 97 88 57 49 24 299
Sara Shahzad Pakistan 11 147 0.9× 81 0.8× 77 0.9× 46 0.8× 14 0.3× 26 299
Niyati Baliyan India 9 151 1.0× 91 0.9× 113 1.3× 16 0.3× 15 0.3× 43 284
Steven A. Demurjian United States 12 217 1.4× 241 2.5× 171 1.9× 32 0.6× 19 0.4× 73 431
Juan Fernández-Olivares Spain 10 47 0.3× 179 1.8× 64 0.7× 20 0.4× 24 0.5× 34 291
Yeong-Tae Song United States 11 173 1.1× 66 0.7× 130 1.5× 35 0.6× 26 0.5× 48 343
Qun Ni United States 12 188 1.2× 377 3.9× 113 1.3× 21 0.4× 20 0.4× 19 580
Baghdad Atmani Algeria 10 71 0.5× 139 1.4× 33 0.4× 63 1.1× 25 0.5× 48 268
Weider D. Yu United States 11 218 1.4× 96 1.0× 115 1.3× 41 0.7× 5 0.1× 41 343
Aprna Tripathi India 8 72 0.5× 91 0.9× 62 0.7× 30 0.5× 5 0.1× 29 221

Countries citing papers authored by Ching-Seh Wu

Since Specialization
Citations

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

Fields of papers citing papers by Ching-Seh Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching-Seh Wu. 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 Ching-Seh Wu. The network helps show where Ching-Seh Wu may publish in the future.

Co-authorship network of co-authors of Ching-Seh Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Ching-Seh Wu. A scholar is included among the top collaborators of Ching-Seh Wu 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 Ching-Seh Wu. Ching-Seh Wu 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.
2.
Wu, Ching-Seh, et al.. (2024). Multi-Label Text Classification with Transfer Learning. 21–26. 1 indexed citations
3.
Wu, Ching-Seh, et al.. (2023). A Heuristic Intrusion Detection Approach Using Deep Learning Model. 438–442. 4 indexed citations
4.
Wu, Ching-Seh, et al.. (2019). Heart Disease Prediction Using Data Mining Techniques. 7–11. 57 indexed citations
5.
Wu, Ching-Seh, et al.. (2019). Analyzing Happiness Index Based on Geographical Locations. 45–51. 3 indexed citations
6.
Wu, Ching-Seh, et al.. (2019). Survey on Anomaly Detection in Wireless Sensor Networks (WSNs). 150–157. 12 indexed citations
7.
8.
Wu, Ching-Seh, et al.. (2018). Movie Recommendation System Using Collaborative Filtering. 11–15. 53 indexed citations
9.
Wu, Ching-Seh, et al.. (2014). A quality-based semantic service broker using reachability indexes. 6. 277–282. 1 indexed citations
10.
11.
Wu, Ching-Seh, et al.. (2013). Web Service Composition: From UML to Optimization. 4. 139–146. 1 indexed citations
12.
Wu, Ching-Seh, et al.. (2013). The Web Services Composition Testing Based on Extended Finite State Machine and UML Model. 5047. 215–222. 4 indexed citations
13.
Wu, Ching-Seh, et al.. (2012). Optimizing Medical Data Quality Based on Multiagent Web Service Framework. IEEE Transactions on Information Technology in Biomedicine. 16(4). 745–757. 7 indexed citations
14.
Wu, Ching-Seh, et al.. (2012). QoS-aware dynamic research component composition for collaborative research projects in the clouds. 4. 883–888. 4 indexed citations
15.
Wu, Ching-Seh, et al.. (2012). E-Healthcare Web Service Broker Infrastructure in Cloud Environment. 8. 317–322. 6 indexed citations
16.
Wu, Ching-Seh, et al.. (2012). Automatic SaaS test cases generation based on SOA in the cloud service. 349–354. 6 indexed citations
17.
Wu, Ching-Seh, Wei‐Chun Chang, & Ishwar K. Sethi. (2009). A Metric-Based Multi-Agent System for Software Project Management. 2. 3–8. 14 indexed citations
18.
Chang, Wei‐Chun, Ching-Seh Wu, & Chun‐Yen Chang. (2005). Optimizing Dynamic Web Service Component Composition by Using Evolutionary Algorithms. 708–711. 18 indexed citations
19.
20.
Wu, Ching-Seh, et al.. (2002). Plan tracking knowledge base. 299–304. 4 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.

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