Deepjyoti Roy
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Topic Modeling
- Sentiment Analysis and Opinion Mining
Papers in
-
- Recommender Systems and Techniques 4
- AI and Big Data Applications 1
-
- Sentiment Analysis and Opinion Mining 4
- Co-authors
- Mala Dutta (5 shared papers)D. R. K. Saikanth (2 shared papers)Anshuman Kumar (1 shared paper)Dipa Islam (1 shared paper)Poonam Sharma (1 shared paper)D. Kumar (1 shared paper)Rajesh Kumar Singh (1 shared paper)Bal Veer Singh (1 shared paper)
- Journals
- Journal Of Big Data (1 paper)Social Network Analysis and Mining (1 paper)Advances in Engineering Software (1 paper)Journal of Information & Knowledge Management (1 paper)Journal of Food Quality and Hazards Control (1 paper)
In The Last Decade
Deepjyoti Roy
12 papers receiving 289 citations
Deepjyoti Roy's Hit Papers
Peers
Comparison fields: 5 of 75
- Information Systems 153
- Artificial Intelligence 112
- Marketing 27
- Computer Science Applications 15
- Computer Vision and Pattern Recognition 48
Countries citing papers authored by Deepjyoti Roy
This map shows the geographic impact of Deepjyoti Roy'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 Deepjyoti Roy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepjyoti Roy more than expected).
Fields of papers citing papers by Deepjyoti Roy
This network shows the impact of papers produced by Deepjyoti Roy. 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 Deepjyoti Roy. The network helps show where Deepjyoti Roy may publish in the future.
Co-authors
The 11 scholars most cited alongside Deepjyoti Roy, 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 | A systematic review and research perspective on recommender systems Hit paper breakdown → | 2022 | 271 |
| 2 | 2022 | 10 | |
| 3 | 2022 | 8 | |
| 4 | 2022 | 8 | |
| 5 | 2023 | 3 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 3 | |
| 8 | 2022 | 2 | |
| 9 | 2023 | 1 | |
| 10 | 2025 | 1 | |
| 11 | 2023 | 1 | |
| 12 | 2020 | 1 |
About Deepjyoti Roy
Deepjyoti Roy is a scholar working on Information Systems, Artificial Intelligence, Molecular Biology, Health Information Management and Cardiology and Cardiovascular Medicine, having authored 12 papers that have together received 312 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (4 papers), Recommender Systems and Techniques (4 papers), Artificial Intelligence in Healthcare (2 papers), RFID technology advancements (1 paper), Meat and Animal Product Quality (1 paper), Food Waste Reduction and Sustainability (1 paper), AI and Big Data Applications (1 paper) and Agricultural Systems and Practices (1 paper). The work is most often cited by research in Information Systems (153 citations), Artificial Intelligence (112 citations), Marketing (27 citations), Computer Science Applications (15 citations) and Computer Vision and Pattern Recognition (48 citations). Deepjyoti Roy has collaborated with scholars based in India, Hungary and Thailand. Frequent co-authors include Mala Dutta, D. R. K. Saikanth, Anshuman Kumar, Dipa Islam, Poonam Sharma, D. Kumar, Rajesh Kumar Singh, Bal Veer Singh, Sadika Akhter and Ankur Saxena. Their work appears in journals such as Journal Of Big Data, Social Network Analysis and Mining, Advances in Engineering Software, Journal of Information & Knowledge Management and Journal of Food Quality and Hazards Control.
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.