V. Uma
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
- Artificial Intelligence top 10%
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
Papers in ⓘ
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- Recommender Systems and Techniques 9
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- Livestock Management and Performance Improvement 15
- Co-authors
- Philomina Simon (3 shared papers)Vishal Vyas (2 shared papers)Ajit Kumar (1 shared paper)Gautam Srivastava (2 shared papers)Mahesh Pathakoti (2 shared papers)G. Aghila (4 shared papers)Kumar Ravi (1 shared paper)Mahalakshmi D.V. (1 shared paper)
In The Last Decade
V. Uma
48 papers receiving 512 citations
Peers
Comparison fields: 5 of 109
- Information Systems 210
- Artificial Intelligence 182
- Computer Vision and Pattern Recognition 104
- Health, Toxicology and Mutagenesis 60
- Management Science and Operations Research 48
Countries citing papers authored by V. Uma
This map shows the geographic impact of V. Uma'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 V. Uma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites V. Uma more than expected).
Fields of papers citing papers by V. Uma
This network shows the impact of papers produced by V. Uma. 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 V. Uma. The network helps show where V. Uma may publish in the future.
Co-authors
The 14 scholars most cited alongside V. Uma, 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 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 52 | |
| 2 | 2020 | 51 | |
| 3 | 2018 | 50 | |
| 4 | 2019 | 44 | |
| 5 | 2022 | 41 | |
| 6 | 2015 | 38 | |
| 7 | 2021 | 28 | |
| 8 | 2018 | 27 | |
| 9 | 2021 | 25 | |
| 10 | 2021 | 20 | |
| 11 | 2021 | 20 | |
| 12 | 2012 | 17 | |
| 13 | 2019 | 16 | |
| 14 | 2019 | 16 | |
| 15 | 2023 | 10 | |
| 16 | Level of participation of women in livestock farming activities. | 2009 | 9 |
| 17 | 2021 | 9 | |
| 18 | 2022 | 8 | |
| 19 | Temporal pattern mining and reasoning using Reference Event based Temporal Relations (RETR) | 2011 | 8 |
| 20 | 2020 | 7 |
About V. Uma
V. Uma is a scholar working on Information Systems, Agronomy and Crop Science, Artificial Intelligence, General Agricultural and Biological Sciences and Computer Networks and Communications, having authored 59 papers that have together received 549 indexed citations. Recurring topics across this work include Livestock Management and Performance Improvement (15 papers), Agricultural Economics and Practices (12 papers), Data Management and Algorithms (11 papers), Recommender Systems and Techniques (9 papers), Agricultural Systems and Practices (8 papers), Constraint Satisfaction and Optimization (7 papers), Semantic Web and Ontologies (5 papers) and Image Retrieval and Classification Techniques (5 papers). The work is most often cited by research in Information Systems (210 citations), Artificial Intelligence (182 citations), Computer Vision and Pattern Recognition (104 citations), Health, Toxicology and Mutagenesis (60 citations) and Management Science and Operations Research (48 citations). V. Uma has collaborated with scholars based in India, Taiwan and Canada. Frequent co-authors include Philomina Simon, Vishal Vyas, Ajit Kumar, Gautam Srivastava, Mahesh Pathakoti, G. Aghila, Kumar Ravi, Mahalakshmi D.V., S. Karthikeyan and S. Sureshkumar. Their work appears in journals such as Journal of King Saud University - Computer and Information Sciences, Sadhana, Health Information Science and Systems, IEEE Access and Atmospheric chemistry and physics.
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.