Prafulla Kumar Choubey
- Artificial Intelligence top 5%
- Management Science and Operations Research top 10%
- Sociology and Political Science
- Computer Vision and Pattern Recognition
- Information Systems
- Topics
- Topic Modeling (18 papers)Natural Language Processing Techniques (17 papers)Advanced Text Analysis Techniques (8 papers)
- Journals
- Language Resources and EvaluationProceedings of the 2021 Conference on Empirical Methods in Natural Language ProcessingInternational Journal for Research in Applied Science and Engineering Technology
- Partner nations
- United StatesIndia
In The Last Decade
Prafulla Kumar Choubey
24 papers receiving 314 citations
Peers
Comparison fields: 5 of 39
- Artificial Intelligence 276
- Management Science and Operations Research 44
- Sociology and Political Science 38
- Computer Vision and Pattern Recognition 38
- Information Systems 35
Countries citing papers authored by Prafulla Kumar Choubey
This map shows the geographic impact of Prafulla Kumar Choubey'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 Prafulla Kumar Choubey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prafulla Kumar Choubey more than expected).
Fields of papers citing papers by Prafulla Kumar Choubey
This network shows the impact of papers produced by Prafulla Kumar Choubey. 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 Prafulla Kumar Choubey. The network helps show where Prafulla Kumar Choubey may publish in the future.
Co-authorship network of co-authors of Prafulla Kumar Choubey
This figure shows the co-authorship network connecting the top 25 collaborators of Prafulla Kumar Choubey. A scholar is included among the top collaborators of Prafulla Kumar Choubey 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 Prafulla Kumar Choubey. Prafulla Kumar Choubey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 7 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 7 | |
| 9 | 1 | |
| 10 | 4 | |
| 11 | 5 | |
| 12 | One Classifier for All Ambiguous Words: Overcoming Data Sparsity by Utilizing Sense Correlations Across Words | 1 |
| 13 | 54 | |
| 14 | 51 | |
| 15 | 21 | |
| 16 | 14 | |
| 17 | 39 | |
| 18 | 5 | |
| 19 | 24 | |
| 20 | 13 |
About Prafulla Kumar Choubey
Prafulla Kumar Choubey is a scholar working on Artificial Intelligence, General Social Sciences and Computer Vision and Pattern Recognition, having authored 26 papers that have together received 328 indexed citations. Recurring topics across this work include Topic Modeling (18 papers), Natural Language Processing Techniques (17 papers) and Advanced Text Analysis Techniques (8 papers). The work is most often cited by research in Artificial Intelligence (276 citations), General Social Sciences (20 citations) and Management Science and Operations Research (44 citations). Prafulla Kumar Choubey has collaborated with scholars based in United States and India. Frequent co-authors include Ruihong Huang, Lei Gao, Aaron Lee, Ruihong Huang, Lu Wang, Eva Sharma, Shubham Pateria, Jesse Vig, Chien-Sheng Wu and Caiming Xiong. Their work appears in journals such as Language Resources and Evaluation, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing and International Journal for Research in Applied Science and Engineering Technology.
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.