S. Sendhilkumar
Impact in
- Artificial Intelligence top 5%
- Advanced Text Analysis Techniques
- Sentiment Analysis and Opinion Mining
- Topic Modeling
- Text and Document Classification Technologies
- General Social Sciences top 5%
Papers in
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- Advanced Text Analysis Techniques 18
- Sentiment Analysis and Opinion Mining 8
- Topic Modeling 6
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- Web Data Mining and Analysis 13
- Recommender Systems and Techniques 8
- Spam and Phishing Detection 5
- Co-authors
- G. S. Mahalakshmi (15 shared papers)T. V. Geetha (6 shared papers)K. Selvakumar (2 shared papers)N. Gnanasekaran (1 shared paper)T. V. Geetha (1 shared paper)S. N. Sivanandam (1 shared paper)M. Senthilkumar (1 shared paper)Pandi Vijayakumar (1 shared paper)
In The Last Decade
S. Sendhilkumar
47 papers receiving 322 citations
Peers
Comparison fields: 5 of 87
- Artificial Intelligence 204
- General Social Sciences 16
- Information Systems 98
- Management Science and Operations Research 41
- Statistical and Nonlinear Physics 36
Countries citing papers authored by S. Sendhilkumar
This map shows the geographic impact of S. Sendhilkumar'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 S. Sendhilkumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Sendhilkumar more than expected).
Fields of papers citing papers by S. Sendhilkumar
This network shows the impact of papers produced by S. Sendhilkumar. 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 S. Sendhilkumar. The network helps show where S. Sendhilkumar may publish in the future.
Co-authors
The 13 scholars most cited alongside S. Sendhilkumar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 93 | |
| 2 | Indian Logic Ontology based Automatic Query Refinement | 2008 | 64 |
| 3 | 2013 | 23 | |
| 4 | 2008 | 15 | |
| 5 | 2011 | 14 | |
| 6 | 2020 | 12 | |
| 7 | 2022 | 12 | |
| 8 | 2018 | 8 | |
| 9 | 2020 | 7 | |
| 10 | 2016 | 7 | |
| 11 | 2017 | 6 | |
| 12 | 2013 | 5 | |
| 13 | 2009 | 5 | |
| 14 | 2020 | 4 | |
| 15 | 2017 | 4 | |
| 16 | 2016 | 4 | |
| 17 | 2009 | 4 | |
| 18 | 2016 | 4 | |
| 19 | 2018 | 4 | |
| 20 | 2016 | 4 |
About S. Sendhilkumar
S. Sendhilkumar is a scholar working on Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics, Signal Processing and Molecular Biology, having authored 49 papers that have together received 352 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (18 papers), Web Data Mining and Analysis (13 papers), Complex Network Analysis Techniques (9 papers), Sentiment Analysis and Opinion Mining (8 papers), Recommender Systems and Techniques (8 papers), Data Management and Algorithms (6 papers), Topic Modeling (6 papers) and Spam and Phishing Detection (5 papers). The work is most often cited by research in Artificial Intelligence (204 citations), General Social Sciences (16 citations), Information Systems (98 citations), Management Science and Operations Research (41 citations) and Statistical and Nonlinear Physics (36 citations). S. Sendhilkumar has collaborated with scholars based in India, China and Cyprus. Frequent co-authors include G. S. Mahalakshmi, T. V. Geetha, K. Selvakumar, N. Gnanasekaran, T. V. Geetha, S. N. Sivanandam, M. Senthilkumar, Pandi Vijayakumar, R. Vijaya Kumar Reddy and Yongxin Zhu. Their work appears in journals such as Expert Systems with Applications, IEEE Transactions on Emerging Topics in Computing, IEEE Transactions on Sustainable Computing, Cognitive Computation and International Journal of Uncertainty Fuzziness and Knowledge-Based Systems.
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.