S. Kannimuthu
- Artificial Intelligence top 10%
- Information Systems top 5%
- Computational Theory and Mathematics top 5%
- Computer Networks and Communications
- Signal Processing top 10%
- Co-authors
- K. PremalathaK. S. BhuvaneshwariD.K. SubramanianShashi Kant ShankarM. Anand KumarM. PrakashShankar SubramanianS. T. Suganthi
- Topics
- Data Mining Algorithms and Applications (12 papers)Rough Sets and Fuzzy Logic (8 papers)Imbalanced Data Classification Techniques (5 papers)
- Partner nations
- IndiaUnited StatesSerbia
In The Last Decade
S. Kannimuthu
40 papers receiving 353 citations
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 189
- Information Systems 156
- Computational Theory and Mathematics 83
- Computer Networks and Communications 48
- Signal Processing 46
Countries citing papers authored by S. Kannimuthu
This map shows the geographic impact of S. Kannimuthu'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. Kannimuthu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Kannimuthu more than expected).
Fields of papers citing papers by S. Kannimuthu
This network shows the impact of papers produced by S. Kannimuthu. 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. Kannimuthu. The network helps show where S. Kannimuthu may publish in the future.
Co-authorship network of co-authors of S. Kannimuthu
This figure shows the co-authorship network connecting the top 25 collaborators of S. Kannimuthu. A scholar is included among the top collaborators of S. Kannimuthu 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 S. Kannimuthu. S. Kannimuthu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 6 | |
| 5 | 8 | |
| 6 | 3 | |
| 7 | 8 | |
| 8 | 4 | |
| 9 | 17 | |
| 10 | 8 | |
| 11 | Machine Learning Based Approach For Corona Virus Disease Recovery Prediction | 2 |
| 12 | 15 | |
| 13 | An Integration of Big Data Analytics and Cyber Security-A Panoramic Survey | 0 |
| 14 | 1 | |
| 15 | KCE DALab-APDA@FIRE2019: Author Profiling and Deception Detection in Arabic using Weighted Embedding. | 1 |
| 16 | KCE_DAlab@MAPonSMS-FIRE2018: Effective word and character-based features for Multilingual Author Profiling. | 1 |
| 17 | 0 | |
| 18 | 28 | |
| 19 | KEC_DAlab @ EventXtract-IL-FIRE2017: Event Extraction using Support Vector Machines. | 1 |
| 20 | A Novel Approach to Extract High Utility Itemsets from Distributed Databases | 9 |
About S. Kannimuthu
S. Kannimuthu is a scholar working on Information Systems, Signal Processing and Artificial Intelligence, having authored 46 papers that have together received 387 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (12 papers), Rough Sets and Fuzzy Logic (8 papers) and Imbalanced Data Classification Techniques (5 papers). The work is most often cited by research in Information Systems (156 citations), Artificial Intelligence (189 citations) and Computational Theory and Mathematics (83 citations). S. Kannimuthu has collaborated with scholars based in India, United States and Serbia. Frequent co-authors include K. Premalatha, K. S. Bhuvaneshwari, D.K. Subramanian, Shashi Kant Shankar, M. Anand Kumar, M. Prakash, Shankar Subramanian, S. T. Suganthi, Nebojša Bačanin and S. Nandhini. Their work appears in journals such as IEEE Access, Biomedical Signal Processing and Control and Mobile Networks and Applications.
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.