Ganesh Chandrasekaran
- Artificial Intelligence top 10%
- Information Systems top 10%
- Sociology and Political Science
- Computer Vision and Pattern Recognition
- Computer Networks and Communications
- Co-authors
- D. Jude HemanthTu N. NguyenDaniela Elena PopescuSanaa KaddouraS. DhanasekaranK. MuneeswaranN. SelvakumarJ. Chinna Babu
- Topics
- Sentiment Analysis and Opinion Mining (6 papers)Advanced Text Analysis Techniques (3 papers)Text and Document Classification Technologies (3 papers)
- Journals
- Applied Soft ComputingApplied SciencesWiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
- Partner nations
- IndiaRomaniaUnited States
In The Last Decade
Ganesh Chandrasekaran
10 papers receiving 226 citations
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 148
- Information Systems 64
- Sociology and Political Science 44
- Computer Vision and Pattern Recognition 32
- Computer Networks and Communications 19
Countries citing papers authored by Ganesh Chandrasekaran
This map shows the geographic impact of Ganesh Chandrasekaran'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 Ganesh Chandrasekaran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ganesh Chandrasekaran more than expected).
Fields of papers citing papers by Ganesh Chandrasekaran
This network shows the impact of papers produced by Ganesh Chandrasekaran. 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 Ganesh Chandrasekaran. The network helps show where Ganesh Chandrasekaran may publish in the future.
Co-authorship network of co-authors of Ganesh Chandrasekaran
This figure shows the co-authorship network connecting the top 25 collaborators of Ganesh Chandrasekaran. A scholar is included among the top collaborators of Ganesh Chandrasekaran 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 Ganesh Chandrasekaran. Ganesh Chandrasekaran is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 15 | |
| 3 | 43 | |
| 4 | 27 | |
| 5 | 54 | |
| 6 | 4 | |
| 7 | 13 | |
| 8 | 89 | |
| 9 | 7 | |
| 10 | 1 |
About Ganesh Chandrasekaran
Ganesh Chandrasekaran is a scholar working on Artificial Intelligence, Media Technology and Information Systems, having authored 10 papers that have together received 254 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (6 papers), Advanced Text Analysis Techniques (3 papers) and Text and Document Classification Technologies (3 papers). The work is most often cited by research in Artificial Intelligence (148 citations), Information Systems (64 citations) and Computational Mathematics (1 citation). Ganesh Chandrasekaran has collaborated with scholars based in India, Romania and United States. Frequent co-authors include D. Jude Hemanth, Tu N. Nguyen, Daniela Elena Popescu, Sanaa Kaddoura, S. Dhanasekaran, K. Muneeswaran, N. Selvakumar, J. Chinna Babu, Ajmeera Kiran and Seifedine Kadry. Their work appears in journals such as Applied Soft Computing, Applied Sciences and Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery.
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.