Sujoy Bag
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
- Marketing top 10%
Papers in
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- Recommender Systems and Techniques 4
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- Image and Video Quality Assessment 2
- Image Retrieval and Classification Techniques 2
- Co-authors
- Manoj Kumar Tiwari (6 shared papers)Sri Krishna Kumar (1 shared paper)Felix T.S. Chan (1 shared paper)Abhijeet Ghadge (3 shared papers)Anjali Awasthi (1 shared paper)Subhas Barman (2 shared papers)Mamata Jenamani (1 shared paper)Mohit Goswami (2 shared papers)
- Journals
- Information Sciences (1 paper)Decision Support Systems (1 paper)Intelligent Systems with Applications (1 paper)International Journal of Retail & Distribution Management (1 paper)Journal of Business Research (1 paper)
- Partner nations
- IndiaUnited KingdomUnited States
In The Last Decade
Sujoy Bag
9 papers receiving 413 citations
Sujoy Bag's Hit Papers
Peers
Comparison fields: 5 of 99
- Information Systems 211
- Marketing 53
- Artificial Intelligence 173
- Management Science and Operations Research 60
- Computer Vision and Pattern Recognition 88
Countries citing papers authored by Sujoy Bag
This map shows the geographic impact of Sujoy Bag'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 Sujoy Bag with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sujoy Bag more than expected).
Fields of papers citing papers by Sujoy Bag
This network shows the impact of papers produced by Sujoy Bag. 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 Sujoy Bag. The network helps show where Sujoy Bag may publish in the future.
Co-authors
The 12 scholars most cited alongside Sujoy Bag, 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 | An efficient recommendation generation using relevant Jaccard similarity Hit paper breakdown → | 2019 | 232 |
| 2 | 2017 | 73 | |
| 3 | 2019 | 44 | |
| 4 | 2019 | 40 | |
| 5 | 2014 | 16 | |
| 6 | 2020 | 14 | |
| 7 | 2015 | 13 | |
| 8 | 2023 | 3 | |
| 9 | 2020 | 1 |
About Sujoy Bag
Sujoy Bag is a scholar working on Information Systems, Computer Vision and Pattern Recognition, Marketing, Management Information Systems and Sociology and Political Science, having authored 9 papers that have together received 436 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (4 papers), Consumer Retail Behavior Studies (3 papers), Image and Video Quality Assessment (2 papers), Technology Adoption and User Behaviour (2 papers), Image Retrieval and Classification Techniques (2 papers), Digital Marketing and Social Media (2 papers), Data Management and Algorithms (1 paper) and Customer Service Quality and Loyalty (1 paper). The work is most often cited by research in Information Systems (211 citations), Marketing (53 citations), Artificial Intelligence (173 citations), Management Science and Operations Research (60 citations) and Computer Vision and Pattern Recognition (88 citations). Sujoy Bag has collaborated with scholars based in India, United Kingdom and United States. Frequent co-authors include Manoj Kumar Tiwari, Sri Krishna Kumar, Felix T.S. Chan, Abhijeet Ghadge, Anjali Awasthi, Subhas Barman, Mamata Jenamani, Mohit Goswami, Samiran Chattopadhyay and Debasis Samanta. Their work appears in journals such as Information Sciences, Decision Support Systems, Intelligent Systems with Applications, International Journal of Retail & Distribution Management and Journal of Business Research.
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.