P. Deepa Shenoy
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computer Networks and Communications top 10%
- Sociology and Political Science
- Computer Vision and Pattern Recognition
- Co-authors
- K R VenugopalL.M. PatnaikK. R. VenugopalSavitha RamasamyK. G. SrinivasaArun Kumar SangaiahSantosh PattarMahesh Mohan
- Topics
- Sentiment Analysis and Opinion Mining (16 papers)Spam and Phishing Detection (12 papers)Network Security and Intrusion Detection (11 papers)
- Partner nations
- IndiaNetherlandsUnited States
In The Last Decade
P. Deepa Shenoy
71 papers receiving 649 citations
Hit Papers
Peers
Comparison fields: 5 of 98
- Artificial Intelligence 439
- Information Systems 187
- Computer Networks and Communications 76
- Sociology and Political Science 70
- Computer Vision and Pattern Recognition 58
Countries citing papers authored by P. Deepa Shenoy
This map shows the geographic impact of P. Deepa Shenoy'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 P. Deepa Shenoy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites P. Deepa Shenoy more than expected).
Fields of papers citing papers by P. Deepa Shenoy
This network shows the impact of papers produced by P. Deepa Shenoy. 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 P. Deepa Shenoy. The network helps show where P. Deepa Shenoy may publish in the future.
Co-authorship network of co-authors of P. Deepa Shenoy
This figure shows the co-authorship network connecting the top 25 collaborators of P. Deepa Shenoy. A scholar is included among the top collaborators of P. Deepa Shenoy 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 P. Deepa Shenoy. P. Deepa Shenoy 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 | 1 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 15 | |
| 9 | 0 | |
| 10 | 5 | |
| 11 | 7 | |
| 12 | 5 | |
| 13 | A Brief Survey on Privacy Preserving Data Mining Techniques | 4 |
| 14 | 11 | |
| 15 | Cancer Prognosis Prediction Model using Data Mining Techniques | 3 |
| 16 | 2 | |
| 17 | 13 | |
| 18 | 7 | |
| 19 | 5 | |
| 20 | 4 |
About P. Deepa Shenoy
P. Deepa Shenoy is a scholar working on Health Information Management, Artificial Intelligence and Information Systems, having authored 77 papers that have together received 698 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (16 papers), Spam and Phishing Detection (12 papers) and Network Security and Intrusion Detection (11 papers). The work is most often cited by research in Artificial Intelligence (439 citations), Information Systems (187 citations) and Health Information Management (35 citations). P. Deepa Shenoy has collaborated with scholars based in India, Netherlands and United States. Frequent co-authors include K R Venugopal, L.M. Patnaik, K. R. Venugopal, Savitha Ramasamy, K. G. Srinivasa, Arun Kumar Sangaiah, K R Venugopal, Santosh Pattar, Mahesh Mohan and Sanjay Sharma. Their work appears in journals such as Computers & Electrical Engineering, Results in Engineering and World Wide Web.
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.