Shampa Chakraverty
- Artificial Intelligence top 10%
- Information Systems top 10%
- Computer Vision and Pattern Recognition top 10%
- Computer Science Applications top 5%
- Experimental and Cognitive Psychology
- Co-authors
- Pinaki ChakrabortyKanika KanikaOm Prakash VermaDevendra K. TayalSanjay MisraRitu SibalDipika JainAnil Kumar
- Topics
- Advanced Text Analysis Techniques (9 papers)Sentiment Analysis and Opinion Mining (7 papers)Advanced Steganography and Watermarking Techniques (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaACM Computing SurveysMeasurement
In The Last Decade
Shampa Chakraverty
51 papers receiving 340 citations
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 143
- Information Systems 95
- Computer Vision and Pattern Recognition 75
- Computer Science Applications 61
- Experimental and Cognitive Psychology 55
Countries citing papers authored by Shampa Chakraverty
This map shows the geographic impact of Shampa Chakraverty'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 Shampa Chakraverty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shampa Chakraverty more than expected).
Fields of papers citing papers by Shampa Chakraverty
This network shows the impact of papers produced by Shampa Chakraverty. 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 Shampa Chakraverty. The network helps show where Shampa Chakraverty may publish in the future.
Co-authorship network of co-authors of Shampa Chakraverty
This figure shows the co-authorship network connecting the top 25 collaborators of Shampa Chakraverty. A scholar is included among the top collaborators of Shampa Chakraverty 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 Shampa Chakraverty. Shampa Chakraverty is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 13 | |
| 3 | 2 | |
| 4 | 9 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 12 | |
| 11 | On using reviews and comments for cross domain recommendations and decision making | 2 |
| 12 | 3 | |
| 13 | 8 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 2 | |
| 17 | Profiling E-Governance Users using Biclustering | 0 |
| 18 | 1 | |
| 19 | 5 | |
| 20 | 3 |
About Shampa Chakraverty
Shampa Chakraverty is a scholar working on Computer Science Applications, Artificial Intelligence and Hardware and Architecture, having authored 52 papers that have together received 359 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (9 papers), Sentiment Analysis and Opinion Mining (7 papers) and Advanced Steganography and Watermarking Techniques (6 papers). The work is most often cited by research in Computer Science Applications (61 citations), Artificial Intelligence (143 citations) and Information Systems (95 citations). Shampa Chakraverty has collaborated with scholars based in India, Canada and Nigeria. Frequent co-authors include Pinaki Chakraborty, Kanika Kanika, Om Prakash Verma, Devendra K. Tayal, Sanjay Misra, Ritu Sibal, Dipika Jain, Anil Kumar, Ashish Sachdeva and Debajyoti Choudhuri. Their work appears in journals such as SHILAP Revista de lepidopterología, ACM Computing Surveys and Measurement.
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.