Chandra Khatri
Impact in
-
- Topic Modeling
- AI in Service Interactions
- Speech and dialogue systems
- Natural Language Processing Techniques
- Speech Recognition and Synthesis
- Sentiment Analysis and Opinion Mining
Papers in
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- Speech and dialogue systems 5
- Topic Modeling 5
- AI in Service Interactions 2
- Advanced Text Analysis Techniques 2
- Semantic Web and Ontologies 2
- Natural Language Processing Techniques 1
- Co-authors
- Raefer Gabriel (3 shared papers)Behnam Hedayatnia (3 shared papers)Ashwin Ram (2 shared papers)Rohit Prasad (2 shared papers)Anu Venkatesh (2 shared papers)Alexandros Papangelis (3 shared papers)Gökhan Tür (3 shared papers)Huaixiu Zheng (3 shared papers)
- Journals
- International Journal of Surgery (1 paper)AI Magazine (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- GermanyUnited StatesChina
In The Last Decade
Chandra Khatri
8 papers receiving 97 citations
Peers
Comparison fields: 5 of 35
- Health Informatics 4
- Artificial Intelligence 88
- Applied Psychology 5
- Social Psychology 18
- Information Systems and Management 6
Countries citing papers authored by Chandra Khatri
This map shows the geographic impact of Chandra Khatri'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 Chandra Khatri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chandra Khatri more than expected).
Fields of papers citing papers by Chandra Khatri
This network shows the impact of papers produced by Chandra Khatri. 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 Chandra Khatri. The network helps show where Chandra Khatri may publish in the future.
Co-authors
The 25 scholars most cited alongside Chandra Khatri, 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 | 2018 | 38 | |
| 2 | 2020 | 27 | |
| 3 | On Evaluating and Comparing Conversational Agents | 2018 | 24 |
| 4 | 2018 | 9 | |
| 5 | 2015 | 5 | |
| 6 | 2017 | 1 | |
| 7 | Commonsense and Semantic-Guided Navigation through Language in Embodied Environment. | 2019 | 1 |
| 8 | Common sense and Semantic-Guided Navigation via Language in Embodied Environments | 2019 | 1 |
| 9 | 2024 | 0 |
About Chandra Khatri
Chandra Khatri is a scholar working on Artificial Intelligence, General Health Professions, Information Systems, Health Informatics and Public Health, Environmental and Occupational Health, having authored 9 papers that have together received 106 indexed citations. Recurring topics across this work include Speech and dialogue systems (5 papers), Topic Modeling (5 papers), AI in Service Interactions (2 papers), Advanced Text Analysis Techniques (2 papers), Semantic Web and Ontologies (2 papers), Artificial Intelligence in Healthcare and Education (1 paper), Web Data Mining and Analysis (1 paper) and Natural Language Processing Techniques (1 paper). The work is most often cited by research in Health Informatics (4 citations), Artificial Intelligence (88 citations), Applied Psychology (5 citations), Social Psychology (18 citations) and Information Systems and Management (6 citations). Chandra Khatri has collaborated with scholars based in Germany, United States and China. Frequent co-authors include Raefer Gabriel, Behnam Hedayatnia, Ashwin Ram, Rohit Prasad, Anu Venkatesh, Alexandros Papangelis, Gökhan Tür, Huaixiu Zheng, Rahul Goel and Piero Molino. Their work appears in journals such as International Journal of Surgery, AI Magazine and arXiv (Cornell University).
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.