Sentiment analysis using common‐sense and context information B Agarwal, N Mittal, P Bansal, S Garg Computational intelligence and neuroscience 2015 (1), 715730, 2015 | 282 | 2015 |
Concept-level sentiment analysis with dependency-based semantic parsing: a novel approach B Agarwal, S Poria, N Mittal, A Gelbukh, A Hussain Cognitive Computation 7, 487-499, 2015 | 172 | 2015 |
Optimizing semantic LSTM for spam detection G Jain, M Sharma, B Agarwal International Journal of Information Technology, 1-12, 2018 | 170 | 2018 |
Spam detection in social media using convolutional and long short term memory neural network G Jain, M Sharma, B Agarwal Annals of Mathematics and Artificial Intelligence 85 (1), 21-44, 2019 | 162 | 2019 |
A deep network model for paraphrase detection in short text messages B Agarwal, H Ramampiaro, H Langseth, M Ruocco Information Processing & Management 54 (6), 922-937, 2018 | 144 | 2018 |
Machine learning approach for sentiment analysis B Agarwal, N Mittal, B Agarwal, N Mittal Prominent feature extraction for sentiment analysis, 21-45, 2016 | 137 | 2016 |
Sentiment analysis of hindi reviews based on negation and discourse relation N Mittal, B Agarwal, G Chouhan, N Bania, P Pareek Proceedings of the 11th workshop on Asian language resources, 45-50, 2013 | 136 | 2013 |
Common sense knowledge based personality recognition from text S Poria, A Gelbukh, B Agarwal, E Cambria, N Howard Advances in Soft Computing and Its Applications: 12th Mexican International …, 2013 | 133 | 2013 |
Hybrid approach for detection of anomaly network traffic using data mining techniques B Agarwal, N Mittal Procedia Technology 6, 996-1003, 2012 | 126 | 2012 |
Text classification using machine learning methods-a survey B Agarwal, N Mittal Proceedings of the Second International Conference on Soft Computing for …, 2014 | 124 | 2014 |
Prominent feature extraction for sentiment analysis B Agarwal, N Mittal Springer International Publishing, 2016 | 115 | 2016 |
Sentiment analysis of social media response on the Covid19 outbreak T Sentiment Brain, behavior, and immunity 87, 136-137, 2020 | 114 | 2020 |
Optimal feature selection for sentiment analysis B Agarwal, N Mittal Computational Linguistics and Intelligent Text Processing: 14th …, 2013 | 97 | 2013 |
Dependency-based semantic parsing for concept-level text analysis S Poria, B Agarwal, A Gelbukh, A Hussain, N Howard Computational Linguistics and Intelligent Text Processing: 15th …, 2014 | 85 | 2014 |
Prominent feature extraction for review analysis: an empirical study B Agarwal, N Mittal Journal of Experimental & Theoretical Artificial Intelligence 28 (3), 485-498, 2016 | 84 | 2016 |
One-shot cluster-based approach for the detection of COVID–19 from chest X–ray images VNM Aradhya, M Mahmud, DS Guru, B Agarwal, MS Kaiser Cognitive Computation 13 (4), 873-881, 2021 | 75 | 2021 |
Deep learning-based approaches for sentiment analysis B Agarwal, R Nayak, N Mittal, S Patnaik Springer 12, 319, 2020 | 73 | 2020 |
Spam detection on social media using semantic convolutional neural network G Jain, M Sharma, B Agarwal International Journal of Knowledge Discovery in Bioinformatics (IJKDB) 8 (1 …, 2018 | 72 | 2018 |
A cross-sectional study of anxiety, stress, perception and mental health towards online learning of school children in India during COVID-19 P Harjule, A Rahman, B Agarwal Journal of Interdisciplinary Mathematics 24 (2), 411-424, 2021 | 63 | 2021 |
Sentiment classification using rough set based hybrid feature selection B Agarwal, N Mittal Proceedings of the 4th workshop on computational approaches to subjectivity …, 2013 | 62 | 2013 |