| Feature selection and ensemble construction: A two-step method for aspect based sentiment analysis MS Akhtar, D Gupta, A Ekbal, P Bhattacharyya Knowledge-Based Systems 125, 116-135, 2017 | 154 | 2017 |
| Pso-asent: Feature selection using particle swarm optimization for aspect based sentiment analysis DK Gupta, KS Reddy, A Ekbal NLDB 2015, 220-233, 2015 | 56* | 2015 |
| IITP: supervised machine learning for aspect based sentiment analysis DK Gupta, A Ekbal SemEval 2014, 2014 | 31 | 2014 |
| MMQA: A multi-domain multi-lingual question-answering framework for English and Hindi D Gupta, S Kumari, A Ekbal, P Bhattacharyya LREC 2018, 2018 | 27 | 2018 |
| A Hybrid Approach for Entity Extraction in Code-Mixed Social Media Data D Gupta, S Tripathi, A Ekbal, P Bhattacharyya CEUR Workshop Proceedings, 66, 2016 | 24 | 2016 |
| A semi-supervised approach to generate the code-mixed text using pre-trained encoder and transfer learning D Gupta, A Ekbal, P Bhattacharyya EMNLP 2020 (Findings), 2267-2280, 2020 | 22 | 2020 |
| Hierarchical deep multi-modal network for medical visual question answering D Gupta, S Suman, A Ekbal Expert Systems with Applications 164, 113993, 2021 | 21 | 2021 |
| Utilizing deep learning with an information retrieval mechanism to provide question answering in restricted domains A Maitra, S Sengupta, GEO Tom, S Podder, R Pujari, D Gupta, A Ekbal, ... US Patent App. 15/988,911, 2018 | 21 | 2018 |
| A deep neural network framework for English Hindi question answering D Gupta, A Ekbal, P Bhattacharyya ACM Transactions - TALLIP 19 (2), 1-22, 2019 | 20 | 2019 |
| Uncovering code-mixed challenges: A framework for linguistically driven question generation and neural based question answering D Gupta, P Lenka, A Ekbal, P Bhattacharyya CoNLL 2018, 119-130, 2018 | 16 | 2018 |
| A deep neural network based approach for entity extraction in code-mixed Indian social media text D Gupta, A Ekbal, P Bhattacharyya LREC 2018, 2018 | 16 | 2018 |
| IIT-UHH at SemEval-2017 Task 3: Exploring Multiple Features for Community Question Answering and Implicit Dialogue Identification T Nandi, C Biemann, SM Yimam, D Gupta, S Kohail, A Ekbal, ... SemEval 2017, 2017 | 15 | 2017 |
| Can taxonomy help? improving semantic question matching using question taxonomy D Gupta, R Pujari, A Ekbal, P Bhattacharyya, A Maitra, T Jain, S Sengupta COLING 2018, 2021 | 14 | 2021 |
| SMPOST: parts of speech tagger for code-mixed indic social media text D Gupta, S Tripathi, A Ekbal, P Bhattacharyya arXiv preprint arXiv:1702.00167, 2017 | 14 | 2017 |
| Machine learning approach for language identification & transliteration DK Gupta, S Kumar, A Ekbal FIRE 2014, 60-64, 2014 | 12 | 2014 |
| Reinforced Multi-task Approach for Multi-hop Question Generation D Gupta, H Chauhan, AR Tej, A Ekbal, P Bhattacharyya COLING 2020, 2020 | 9 | 2020 |
| Opinion Mining in a Code-Mixed Environment: A Case Study with Government Portals AEPB Deepak Gupta, Ankit Lamba ICON 2016, 249-258, 2016 | 9* | 2016 |
| Combining graph-based dependency features with convolutional neural network for answer triggering D Gupta, S Kohail, P Bhattacharyya CiCLING 2018, 2018 | 7 | 2018 |
| Question-aware transformer models for consumer health question summarization S Yadav, D Gupta, AB Abacha, D Demner-Fushman Journal of Biomedical Informatics 128, 104040, 2022 | 6 | 2022 |
| NLM at MEDIQA 2021: Transfer Learning-based Approaches for Consumer Question and Multi-Answer Summarization S Yadav, M Sarrouti, D Gupta BioNLP-NAACL 2021, 291-301, 2021 | 6 | 2021 |
Asif EkbalDepartment of Computer Science and Engineering, IIT Patna, IndiaVerified email at iitp.ac.in
