Prodip Hore
Impact in
- Artificial Intelligence top 5%
- Advanced Clustering Algorithms Research
- Data Stream Mining Techniques
- Text and Document Classification Technologies
- Anomaly Detection Techniques and Applications
- Signal Processing top 10%
- Data Management and Algorithms
Papers in
-
- Advanced Clustering Algorithms Research 7
- Data Stream Mining Techniques 6
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- Data Management and Algorithms 4
- Co-authors
- Lawrence Hall (8 shared papers)Dmitry B. Goldgof (6 shared papers)D. Goldgof (1 shared paper)Irene Yu‐Hua Gu (1 shared paper)Ammar Darkazanli (1 shared paper)Andrew A. Maudsley (1 shared paper)
- Journals
- Pattern Recognition (1 paper)Journal of Signal Processing Systems (1 paper)Proceedings of ... IEEE International Conference on Fuzzy Systems (1 paper)
- Partner nations
- United States
In The Last Decade
Prodip Hore
8 papers receiving 305 citations
Peers
Comparison fields: 5 of 41
- Artificial Intelligence 268
- Signal Processing 84
- Computer Vision and Pattern Recognition 138
- Computational Mathematics 2
- Statistical and Nonlinear Physics 41
Countries citing papers authored by Prodip Hore
This map shows the geographic impact of Prodip Hore'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 Prodip Hore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prodip Hore more than expected).
Fields of papers citing papers by Prodip Hore
This network shows the impact of papers produced by Prodip Hore. 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 Prodip Hore. The network helps show where Prodip Hore may publish in the future.
Co-authors
The 6 scholars most cited alongside Prodip Hore, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 90 | |
| 2 | 2008 | 74 | |
| 3 | 2008 | 54 | |
| 4 | 2008 | 42 | |
| 5 | 2006 | 20 | |
| 6 | 2007 | 19 | |
| 7 | 2007 | 16 | |
| 8 | Scalable frameworks and algorithms for cluster ensembles and clustering data streams | 2007 | 4 |
About Prodip Hore
Prodip Hore is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Computational Theory and Mathematics, having authored 8 papers that have together received 319 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (7 papers), Data Stream Mining Techniques (6 papers), Data Management and Algorithms (4 papers), Complex Network Analysis Techniques (2 papers), Face and Expression Recognition (2 papers), Medical Image Segmentation Techniques (1 paper), Image Retrieval and Classification Techniques (1 paper) and Rough Sets and Fuzzy Logic (1 paper). The work is most often cited by research in Artificial Intelligence (268 citations), Signal Processing (84 citations), Computer Vision and Pattern Recognition (138 citations), Computational Mathematics (2 citations) and Statistical and Nonlinear Physics (41 citations). Prodip Hore has collaborated with scholars based in United States. Frequent co-authors include Lawrence Hall, Dmitry B. Goldgof, D. Goldgof, Irene Yu‐Hua Gu, Ammar Darkazanli and Andrew A. Maudsley. Their work appears in journals such as Pattern Recognition, Journal of Signal Processing Systems and Proceedings of ... IEEE International Conference on Fuzzy Systems.
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.