| Understanding emotions in text using deep learning and big data A Chatterjee, U Gupta, MK Chinnakotla, R Srikanth, M Galley, P Agrawal Computers in Human Behavior 93, 309-317, 2019 | 356 | 2019 |
| SemEval-2019 task 3: EmoContext contextual emotion detection in text A Chatterjee, KN Narahari, M Joshi, P Agrawal Proceedings of the 13th international workshop on semantic evaluation, 39-48, 2019 | 290 | 2019 |
| A sentiment-and-semantics-based approach for emotion detection in textual conversations U Gupta, A Chatterjee, R Srikanth, P Agrawal arXiv preprint arXiv:1707.06996, 2017 | 103 | 2017 |
| Compression of deep learning models for text: A survey M Gupta, P Agrawal ACM Transactions on Knowledge Discovery from Data (TKDD) 16 (4), 1-55, 2022 | 89 | 2022 |
| Emulating human conversations using convolutional neural network-based IR A Prakash, C Brockett, P Agrawal arXiv preprint arXiv:1606.07056, 2016 | 25 | 2016 |
| Application of breadcrumbs in ranking and search experiences V Krishnan, P Agrawal, A Khator, SH Nagaralu US Patent 8,583,622, 2013 | 20 | 2013 |
| Presenting search results based upon subject-versions SH Nagaralu, P Agrawal, AK Singla, V Krishnan US Patent 9,208,236, 2015 | 17 | 2015 |
| Optimized transformer models for faq answering S Damani, KN Narahari, A Chatterjee, M Gupta, P Agrawal Pacific-Asia Conference on Knowledge Discovery and Data Mining, 235-248, 2020 | 16 | 2020 |
| Map-based selection of query component SH Nagaralu, P Agrawal, V Krishnan US Patent 8,880,496, 2014 | 9 | 2014 |
| FAQaugmenter: suggesting questions for enterprise FAQ pages A Chatterjee, M Gupta, P Agrawal Proceedings of the 13th international conference on web search and data …, 2020 | 7 | 2020 |
| Insights from building an open-ended conversational agent K Gupta, M Joshi, A Chatterjee, S Damani, KN Narahari, P Agrawal Proceedings of the First Workshop on NLP for Conversational AI, 106-112, 2019 | 7 | 2019 |
| Lessons from building a large-scale commercial IR-based chatbot for an emerging market MK Chinnakotla, P Agrawal The 41st International ACM SIGIR Conference on Research & Development in …, 2018 | 6 | 2018 |
| Ruuh: A deep learning based conversational social agent S Damani, N Raviprakash, U Gupta, A Chatterjee, M Joshi, K Gupta, ... arXiv preprint arXiv:1810.12097, 2018 | 4 | 2018 |
| Using AI for Economic Upliftment of Handicraft Industry N Raviprakash, S Damani, A Chatterjee, M Joshi, P Agrawal arXiv preprint arXiv:1907.02014, 2019 | 3 | 2019 |
| Deep learning methods for query auto completion M Gupta, M Joshi, P Agrawal European Conference on Information Retrieval, 341-348, 2023 | 1 | 2023 |
| Emotionally connected responses from a digital assistant P Agrawal US Patent 10,437,615, 2019 | 1 | 2019 |
| Clustering suggestions for partial query auto-completion M Gupta, P Agrawal US Patent App. 17/833,180, 2023 | | 2023 |
| trie-nlg: trie context augmentation to improve personalized query auto-completion for short and unseen prefixes KK Maurya, MS Desarkar, M Gupta, P Agrawal Data Mining and Knowledge Discovery 37 (6), 2306-2329, 2023 | | 2023 |
| Query-Document Topic Mismatch Detection S Chelaramani, A Chatterjee, S Damani, KN Narahari, M Joshi, M Gupta, ... International Conference on Database Systems for Advanced Applications, 413-424, 2022 | | 2022 |
| A Case Study on using Crowdsourcing for Ambiguous Tasks PA Ankush Chatterjee, Umang Gupta IJCCI 2018 : 10th International Joint Conference on Computational Intelligence, 2018 | | 2018 |
