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Author Title [ Year(Asc)]
Sherif, R. El, A. Langlois, P. Du, J-Y. Nie, J. Thomas, Q. Nha Hong, and P. Pluye, "Identifying empirical studies for mixed studies reviews: The mixed filter and the automated text classifier", Education for Information: IOS Press, pp. 1–5, 2020.
Wang, S., P. Ren, Z. Chen, Z. Ren, J-Y. Nie, J. Ma, and M. de Rijke, Coding Electronic Health Records with Adversarial Reinforcement Path Generation, , 2020. pdf
Zhao, K., T. Bai, B. Wu, B. Wang, Y. Zhang, Y. Yang, and J-Y. Nie, "Deep Adversarial Completion for Sparse Heterogeneous Information Network Embedding", Proceedings of The Web Conference 2020, New York, NY, USA, Association for Computing Machinery, 2020. pdf
Zhu, Y., R. Song, Z. Dou, J-Y. Nie, and J. Zhou, "ScriptWriter: Narrative-Guided Script Generation", arXiv preprint arXiv:2005.10331, 2020. pdf
Zhu, Y., Z. Dou, J-Y. Nie, and J-R. Wen, "ReBoost: a retrieval-boosted sequence-to-sequence model for neural response generation", Information Retrieval Journal, vol. 23: Springer, pp. 27–48, 2020. pdf
Zou, L., L. Xia, P. Du, Z. Zhang, T. Bai, W. Liu, J-Y. Nie, and D. Yin, "Pseudo Dyna-Q: A Reinforcement Learning Framework for Interactive Recommendation", Proceedings of the 13th International Conference on Web Search and Data Mining, 2020. pdf
Abiteboul, S., M. Arenas, P. Barceló, M. Bienvenu, D. Calvanese, C. David, R. Hull, E. Hüllermeier, B. Kimelfeld, L. Libkin, et al., Dagstuhl Manifestos, Vol. 7, Issue 1 ISSN 2193-2433, , 2019.
Alfonso-Hermelo, D., P. Langlais, and L. Bourg, "Automatically Learning a Human-Resource Ontology from Professional Social-Network Data", Advances in Artificial Intelligence, Cham, Springer International Publishing, 2019. pdf
Bai, T., W. Xin Zhao, Y. He, J-Y. Nie, and J-R. Wen, "Correction to “Characterizing and Predicting Early Reviewers for Effective Product Marketing on E-Commerce Websites”", IEEE Transactions on Knowledge and Data Engineering, vol. 31: IEEE, pp. 818–818, 2019.
Bai, T., L. Zou, W. Xin Zhao, P. Du, W. Liu, J-Y. Nie, and J-R. Wen, "CTRec: A Long-Short Demands Evolution Model for Continuous-Time Recommendation", Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019.
Bai, T., P. Du, W. Xin Zhao, J-R. Wen, and J-Y. Nie, "A Long-Short Demands-Aware Model for Next-Item Recommendation", arXiv preprint arXiv:1903.00066, 2019.
Bellot, P., L. Cappellato, N. Ferro, J. Mothe, F. Murtagh, J-Y. Nie, E. SanJuan, L. Soulier, and C. Trabelsi, "Report on CLEF 2018: Experimental IR Meets Multilinguality, Multimodality, and Interaction", ACM SIGIR Forum: ACM, 2019.
Ghaddar, A., and P. Langlais, "Contextualized Word Representations from Distant Supervision with and for NER", Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019), Hong Kong, China, Association for Computational Linguistics, 2019. pdf
Gotti, F., and P. Langlais, "Weakly Supervised, Data-Driven Acquisition of Rules for Open Information Extraction", 32nd Canadian Conference on Artificial Intelligence: Springer, pp. 16--28, 06/2019. pdf
Lapalme, G., Verbalizing AMR Structures, , Montréal , RALI-DIRO, pp. 35 pages, 08/2019. pdf
Lapalme, G., Realizing Universal Dependencies Structures, , RALI-DIRO, pp. 26 pages, 10/2019. pdf
Lapalme, G., "Realizing Universal Dependencies Structures using a symbolic approach", The Second Multilingual Surface Realisation Shared Task (SR'19) , Hong-Kong, EMNLP-2019, 11/2019. pdf
Léchelle, W., "Protocoles d’évaluation pour l’extraction d’information libre", DIRO, vol. Ph.D., Montreal, pp. 142, 10/2019. pdf
Levreault, J-G., "Ontomic, une ontologie pour la microbiologie clinique", DIRO, vol. M.Sc., pp. 231, 01/2019. pdf
Lu, S., Z. Dou, X. Jun, J-Y. Nie, and J-R. Wen, "PSGAN: A Minimax Game for Personalized Search with Limited and Noisy Click Data", Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval: ACM, 2019.
Lu, Z., and J-Y. Nie, "RALIGRAPH at HASOC 2019: VGCN-BERT: Augmenting BERT with Graph Embedding for Offensive Language Detection", Proceedings of the 11th annual meeting of the Forum for Information Retrieval Evaluation (December 2019), 2019.
Lu, P., T. Bai, and P. Langlais, "SC-LSTM: Learning Task-Specific Representations in Multi-Task Learning for Sequence Labeling", Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), 2019.
Nie, Y., J. Zhang, and J-Y. Nie, "Integrated Learning of Features and Ranking Function in Information Retrieval", Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval, New York, NY, USA, ACM, 2019. pdf
Piedboeuf, F., P. Langlais, and L. Bourg, "Personality Extraction Through LinkedIn", Advances in Artificial Intelligence, Cham, Springer International Publishing, 2019. pdf
Soliman, Z., P. Langlais, and L. Bourg, "Learning Career Progression by Mining Social Media Profiles", Advances in Artificial Intelligence, Cham, Springer International Publishing, 2019. pdf