Diptesh Kanojia
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition
- Information Systems
- Human-Computer Interaction
- Molecular Biology
- Co-authors
- Pushpak BhattacharyyaAbhijit MishraKuntal DeySeema NagarShehzaad DhuliawalaConstantin OrǎsanAditya JoshiMark Carman
- Topics
- Natural Language Processing Techniques (31 papers)Topic Modeling (22 papers)Sentiment Analysis and Opinion Mining (7 papers)
- Partner nations
- IndiaUnited KingdomAustralia
In The Last Decade
Diptesh Kanojia
38 papers receiving 233 citations
Peers
Comparison fields: 5 of 37
- Artificial Intelligence 208
- Computer Vision and Pattern Recognition 43
- Information Systems 25
- Human-Computer Interaction 24
- Molecular Biology 23
Countries citing papers authored by Diptesh Kanojia
This map shows the geographic impact of Diptesh Kanojia'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 Diptesh Kanojia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diptesh Kanojia more than expected).
Fields of papers citing papers by Diptesh Kanojia
This network shows the impact of papers produced by Diptesh Kanojia. 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 Diptesh Kanojia. The network helps show where Diptesh Kanojia may publish in the future.
Co-authorship network of co-authors of Diptesh Kanojia
This figure shows the co-authorship network connecting the top 25 collaborators of Diptesh Kanojia. A scholar is included among the top collaborators of Diptesh Kanojia 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 Diptesh Kanojia. Diptesh Kanojia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 5 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 9 | |
| 9 | 1 | |
| 10 | 9 | |
| 11 | 14 | |
| 12 | 0 | |
| 13 | 0 | |
| 14 | 37 | |
| 15 | That'll do fine! A coarse lexical resource for English-Hindi MT, using polylingual topic models | 2 |
| 16 | SlangNet: A WordNet like resource for English Slang. | 15 |
| 17 | Using Multilingual Topic Models for Improved Alignment in English-Hindi MT | 1 |
| 18 | PaCMan : Parallel Corpus Management Workbench | 1 |
| 19 | More than meets the eye: Study of Human Cognition in Sense Annotation | 10 |
| 20 | Discrimination-Net for Hindi | 1 |
About Diptesh Kanojia
Diptesh Kanojia is a scholar working on Artificial Intelligence, Communication and Cultural Studies, having authored 50 papers that have together received 246 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (31 papers), Topic Modeling (22 papers) and Sentiment Analysis and Opinion Mining (7 papers). The work is most often cited by research in Artificial Intelligence (208 citations), Human-Computer Interaction (24 citations) and Computer Vision and Pattern Recognition (43 citations). Diptesh Kanojia has collaborated with scholars based in India, United Kingdom and Australia. Frequent co-authors include Pushpak Bhattacharyya, Abhijit Mishra, Kuntal Dey, Seema Nagar, Shehzaad Dhuliawala, Constantin Orǎsan, Aditya Joshi, Mark Carman, Raj Dabre and Tânia Vaz. Their work appears in journals such as ACM Computing Surveys, Language Resources and Evaluation and Information.
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.