| SenticNet 7: A Commonsense-based Neurosymbolic AI Framework for Explainable Sentiment Analysis E Cambria, Q Liu, S Decherchi, F Xing, K Kwok Proceedings of LREC, 2022 | 195 | 2022 |
| Does deep learning help topic extraction? A kernel k-means clustering method with word embedding Y Zhang, J Lu, F Liu, Q Liu, A Porter, H Chen, G Zhang Journal of Informetrics 12 (4), 1099-1117, 2018 | 115 | 2018 |
| The Biases of Pre-Trained Language Models: An Empirical Study on Prompt-Based Sentiment Analysis and Emotion Detection R Mao, Q Liu, K He, W Li, E Cambria IEEE Transactions on Affective Computing, 2022 | 84 | 2022 |
| Task-oriented word embedding for text classification Q Liu, HY Huang, Y Gao, X Wei, Y Tian, L Liu Proceedings of the 27th International Conference on Computational …, 2018 | 62 | 2018 |
| Concept representation by learning explicit and implicit concept couplings W Lu, Y Zhang, S Wang, H Huang, Q Liu, S Luo IEEE Intelligent Systems 36 (1), 6-15, 2020 | 30 | 2020 |
| Semantic structure-based word embedding by incorporating concept convergence and word divergence Q Liu, H Huang, G Zhang, Y Gao, J Xuan, J Lu Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 25 | 2018 |
| Jointly learning topics in sentence embedding for document summarization Y Gao, Y Xu, H Huang, Q Liu, L Wei, L Liu IEEE Transactions on Knowledge and Data Engineering 32 (4), 688-699, 2019 | 24 | 2019 |
| Enhanced word embedding similarity measures using fuzzy rules for query expansion Q Liu, H Huang, J Lu, Y Gao, G Zhang 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-6, 2017 | 23 | 2017 |
| Domain-specific meta-embedding with latent semantic structures Q Liu, J Lu, G Zhang, T Shen, Z Zhang, H Huang Information Sciences 555, 410-423, 2021 | 18 | 2021 |
| Sentic Parser: A Graph-Based Approach to Concept Extraction for Sentiment Analysis E Cambria, R Mao, S Han, Q Liu Proceedings of ICDM Workshops, 2022 | 17 | 2022 |
| A Fuzzy Word Similarity Measure for Selecting Top-k Similar Words in Query Expansion Q Liu, H Huang, J Xuan, G Zhang, Y Gao, J Lu IEEE Transactions on Fuzzy Systems, 2020 | 17 | 2020 |
| Semantic matching in machine reading comprehension: An empirical study Q Liu, R Mao, X Geng, E Cambria Information Processing and Management 2023, 2023 | 9 | 2023 |
| Stress Detection from Social Media Articles: New Dataset Benchmark and Analytical Study A Rastogi, Q Liu, E Cambria Proceedings of IJCNN, 2022 | 9 | 2022 |
| Saving Earth One Tweet at a Time through the Lens of Artificial Intelligence C Duong, Q Liu, R Mao, E Cambria Proceedings of IJCNN, 2022 | 7 | 2022 |
| MGRC: An End-to-End Multigranularity Reading Comprehension Model for Question Answering Q Liu, X Geng, H Huang, T Qin, J Lu, D Jiang IEEE Transactions on Neural Networks and Learning Systems, 2021 | 6 | 2021 |
| Domain structure-based transfer learning for cross-domain word representation H Huang, Q Liu Information Fusion, 2021 | 4 | 2021 |
| A Pairwise Probe for Understanding BERT Fine-Tuning on Machine Reading Comprehension J Cai, Z Zhu, P Nie, Q Liu International ACM SIGIR Conference on Research and Development in …, 2020 | 4 | 2020 |
| Automated Pipeline for Sentiment Analysis of Political Tweets A Das, KS Gunturi, A Chandrasekhar, A Padhi, Q Liu 2021 International Conference on Data Mining Workshops (ICDMW), 128-135, 2021 | 3 | 2021 |
| Leveraging pattern associations for word embedding models Q Liu, H Huang, Y Gao, X Wei, R Geng International Conference on Database Systems for Advanced Applications, 423-438, 2017 | 3 | 2017 |
| Disentangled Retrieval and Reasoning for Implicit Question Answering Q Liu, X Geng, Y Wang, E Cambria, D Jiang IEEE Transactions on Neural Networks and Learning Systems, 2022 | 2 | 2022 |
Erik CambriaProfessor of Computer Science & Engineering, NTU SingaporeVerified email at ntu.edu.sg
