Recent trends in deep learning based natural language processing T Young, D Hazarika, S Poria, E Cambria ieee Computational intelligenCe magazine 13 (3), 55-75, 2018 | 3770 | 2018 |
Tensor fusion network for multimodal sentiment analysis A Zadeh, M Chen, S Poria, E Cambria, LP Morency EMNLP, 2017 | 1398 | 2017 |
A review of affective computing: From unimodal analysis to multimodal fusion S Poria, E Cambria, R Bajpai, A Hussain Information fusion 37, 98-125, 2017 | 1393 | 2017 |
Multimodal language analysis in the wild: Cmu-mosei dataset and interpretable dynamic fusion graph AAB Zadeh, PP Liang, S Poria, E Cambria, LP Morency Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 1015 | 2018 |
Meld: A multimodal multi-party dataset for emotion recognition in conversations S Poria, D Hazarika, N Majumder, G Naik, E Cambria, R Mihalcea Association for Computational Linguistics, 2019 | 979 | 2019 |
Aspect extraction for opinion mining with a deep convolutional neural network S Poria, E Cambria, A Gelbukh Knowledge-Based Systems 108, 42-49, 2016 | 970 | 2016 |
Context-dependent sentiment analysis in user-generated videos S Poria, E Cambria, D Hazarika, N Majumder, A Zadeh, LP Morency Proceedings of the 55th annual meeting of the association for computational …, 2017 | 837 | 2017 |
Dialoguernn: An attentive rnn for emotion detection in conversations N Majumder, S Poria, D Hazarika, R Mihalcea, A Gelbukh, E Cambria Proceedings of the AAAI conference on artificial intelligence 33 (01), 6818-6825, 2019 | 716 | 2019 |
Memory fusion network for multi-view sequential learning A Zadeh, PP Liang, N Mazumder, S Poria, E Cambria, LP Morency Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 698 | 2018 |
Convolutional MKL based multimodal emotion recognition and sentiment analysis S Poria, I Chaturvedi, E Cambria, A Hussain 2016 IEEE 16th international conference on data mining (ICDM), 439-448, 2016 | 653 | 2016 |
Deep learning-based document modeling for personality detection from text N Majumder, S Poria, A Gelbukh, E Cambria IEEE Intelligent Systems 32 (2), 74-79, 2017 | 620 | 2017 |
Deep convolutional neural network textual features and multiple kernel learning for utterance-level multimodal sentiment analysis S Poria, E Cambria, A Gelbukh Proceedings of the 2015 conference on empirical methods in natural language …, 2015 | 586 | 2015 |
Fusing audio, visual and textual clues for sentiment analysis from multimodal content S Poria, E Cambria, N Howard, GB Huang, A Hussain Neurocomputing 174, 50-59, 2016 | 576 | 2016 |
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation D Ghosal, N Majumder, S Poria, N Chhaya, A Gelbukh EMNLP, 2019 | 549 | 2019 |
Misa: Modality-invariant and-specific representations for multimodal sentiment analysis D Hazarika, R Zimmermann, S Poria Proceedings of the 28th ACM international conference on multimedia, 1122-1131, 2020 | 514 | 2020 |
Multi-attention recurrent network for human communication comprehension A Zadeh, PP Liang, S Poria, P Vij, E Cambria, LP Morency Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 488 | 2018 |
SenticNet 6: Ensemble application of symbolic and subsymbolic AI for sentiment analysis E Cambria, Y Li, FZ Xing, S Poria, K Kwok Proceedings of the 29th ACM international conference on information …, 2020 | 475 | 2020 |
SenticNet 5: discovering conceptual primitives for sentiment analysis by means of context embeddings E Cambria, S Poria, D Hazarika, K Kwok Proceedings of AAAI, 2018 | 468 | 2018 |
Sentiment analysis is a big suitcase E Cambria, S Poria, A Gelbukh, M Thelwall IEEE Intelligent Systems 32 (6), 74-80, 2017 | 462 | 2017 |
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos D Hazarika, S Poria, A Zadeh, E Cambria, LP Morency, R Zimmermann Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 445 | 2018 |