P. Accorsi, N. Patel, C. Lopez, R. Panckhurst, and M. Roche, Seek&Hide, Lingvisticae Investigationes, vol.35, issue.2, pp.163-180, 2012.
DOI : 10.1075/bct.61.03acc

URL : https://hal.archives-ouvertes.fr/lirmm-00816272

N. Afzal, Y. Wang, and H. Liu, MayoNLP at SemEval-2016 Task 1: Semantic Textual Similarity based on Lexical Semantic Net and Deep Learning Semantic Model, Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), pp.674-679, 2016.
DOI : 10.18653/v1/S16-1103

R. F. Baumeister, E. Bratslavsky, C. Finkenauer, and K. D. Vohs, Bad is stronger than good., Review of General Psychology, vol.5, issue.4, p.323, 2001.
DOI : 10.1037/1089-2680.5.4.323

D. Bernhard and I. Gurevych, Answering learners' questions by retrieving question paraphrases from social Q&A sites, Proceedings of the Third Workshop on Innovative Use of NLP for Building Educational Applications, EANL '08, pp.44-52, 2008.
DOI : 10.3115/1631836.1631842

URL : https://hal.archives-ouvertes.fr/hal-00800310

D. M. Bikel, R. Schwartz, and R. M. Weischedel, An algorithm that learns what's in a name, Machine Learning, vol.34, issue.1/3, pp.211-231, 1999.
DOI : 10.1023/A:1007558221122

D. Bogdanova, C. N. Dos-santos, L. Barbosa, and B. Zadrozny, Detecting Semantically Equivalent Questions in Online User Forums, Proceedings of the Nineteenth Conference on Computational Natural Language Learning, pp.123-131, 2015.
DOI : 10.18653/v1/K15-1013

URL : https://doi.org/10.18653/v1/k15-1013

P. Denis and B. Sagot, Coupling an annotated corpus and a lexicon for state-of-the-art pos tagging. Language resources and evaluation, pp.721-736, 2012.
DOI : 10.1007/s10579-012-9193-0

URL : https://hal.archives-ouvertes.fr/inria-00614819

M. Feng, B. Xiang, M. R. Glass, L. Wang, and B. Zhou, Applying deep learning to answer selection: A study and an open task, 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), pp.813-820, 2015.
DOI : 10.1109/ASRU.2015.7404872

URL : http://arxiv.org/pdf/1508.01585

Y. Goldberg, Neural Network Methods for Natural Language Processing, Synthesis Lectures on Human Language Technologies, vol.37, issue.1, 2017.
DOI : 10.1111/j.1467-9868.2005.00503.x

R. Higashinaka, Y. Minami, K. Dohsaka, and T. Meguro, Issues in predicting user satisfaction transitions in dialogues: Individual differences, evaluation criteria, and prediction models. In: Spoken Dialogue Systems for Ambient Environments, pp.48-60, 2010.
DOI : 10.1007/978-3-642-16202-2_5

D. Hogan, J. Leveling, H. Wang, P. Ferguson, and C. Gurrin, Dcu@ fire 2011: Sms-based faq retrieval, 3rd Workshop of the Forum for Information Retrieval Evaluation, FIRE. pp, pp.2-4, 2011.

K. S. Hone and R. Graham, Subjective assessment of speech-system interface usability, pp.2083-2086, 2001.

N. Jalbert and W. Weimer, Automated duplicate detection for bug tracking systems, 2008 IEEE International Conference on Dependable Systems and Networks With FTCS and DCC (DSN), pp.52-61, 2008.
DOI : 10.1109/DSN.2008.4630070

URL : http://www.cs.virginia.edu/~weimer/p/weimer-dsn2008-preprint.pdf

J. Jeon, W. B. Croft, and J. H. Lee, Finding semantically similar questions based on their answers, Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '05, pp.617-618, 2005.
DOI : 10.1145/1076034.1076156

URL : http://ciir.cs.umass.edu/pubfiles/ir-410.pdf

V. Jijkoun and M. De-rijke, Retrieving answers from frequently asked questions pages on the web, Proceedings of the 14th ACM international conference on Information and knowledge management , CIKM '05, pp.76-83, 2005.
DOI : 10.1145/1099554.1099571

URL : http://www.science.uva.nl/~mdr/Publications/Files/cikm2005-faqs.pdf

Y. Kim, Convolutional neural networks for sentence classification. arXiv preprint arXiv:1408, p.5882, 2014.
DOI : 10.3115/v1/d14-1181

URL : http://arxiv.org/pdf/1408.5882

Y. Kim, Convolutional Neural Networks for Sentence Classification, Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.1746-1751, 2014.
DOI : 10.3115/v1/D14-1181

URL : http://arxiv.org/pdf/1408.5882

C. W. Liu, R. Lowe, I. V. Serban, M. Noseworthy, L. Charlin et al., How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation, Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016.
DOI : 10.18653/v1/D16-1230

URL : http://arxiv.org/pdf/1603.08023

R. Lowe, I. V. Serban, M. Noseworthy, L. Charlin, and J. Pineau, On the evaluation of dialogue systems with next utterance classification. arXiv preprint, 2016.
DOI : 10.18653/v1/w16-3634

URL : https://doi.org/10.18653/v1/w16-3634

P. Malakasiotis and I. Androutsopoulos, Learning textual entailment using SVMs and string similarity measures, Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, RTE '07, pp.42-47, 2007.
DOI : 10.3115/1654536.1654547

URL : http://www.aueb.gr/users/ion/docs/rte3_paper.pdf

C. D. Manning, P. Raghavan, and H. Schütze, Introduction to information retrieval, vol.1, 2008.

K. Muthmann and A. Petrova, An automatic approach for identifying topical near-duplicate relations between questions from social media q/a sites, Proceeding of WSDM 2014 Workshop: Web-Scale Classification: Classifying Big Data from the Web, 2014.

D. Reitter and J. D. Moore, Predicting success in dialogue, Proceedings of the 45th Annual Meeting of the ACL, 2007.

A. Ritter, C. Cherry, and W. B. Dolan, Data-driven response generation in social media, Proceedings of the conference on empirical methods in natural language processing, pp.583-593, 2011.

J. Rodrigues, C. Saedi, V. Maraev, J. Silva, and A. Branco, Ways of asking and replying in duplicate question detection, 2017.

D. Seddah, B. Sagot, M. Candito, V. Mouilleron, and V. Combet, The french social media bank: a treebank of noisy user generated content, COLING 2012-24th International Conference on Computational Linguistics, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00780898

O. Vinyals and Q. Le, A neural conversational model. arXiv preprint, 2015.

M. Walker, I. Langkilde, J. Wright, A. Gorin, and D. Litman, Learning to predict problematic situations in a spoken dialogue system: experiments with how may I help you?, Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference, pp.210-217, 2000.

M. A. Walker, D. J. Litman, C. A. Kamm, and A. Abella, Paradise: A framework for evaluating spoken dialogue agents, Proceedings of the eighth conference on European chapter of the Association for Computational Linguistics, pp.271-280, 1997.

Y. Wu, Q. Zhang, and X. Huang, Efficient near-duplicate detection for q&a forum, Fifth International Joint Conference on Natural Language Processing, pp.1001-1009, 2011.

X. Xue, J. Jeon, and W. B. Croft, Retrieval models for question and answer archives, Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '08, pp.475-482, 2008.
DOI : 10.1145/1390334.1390416

W. Yin, H. Schütze, B. Xiang, and B. Zhou, Abcnn: Attention-based convolutional neural network for modeling sentence pairs. arXiv preprint, 2015.