B. Dixit, the improved Query DSL, Mastering Elasticsearch 5.x, pp.74-141, 2017.

M. Hagen and C. Glimm, Supporting More-Like-This Information Needs: Finding Similar Web Content in Different Scenarios, Information Access Evaluation. Multilinguality, Multimodality, and Interaction -5th International Conference of the CLEF Initiative Proceedings, ser. Lecture Notes in Computer Science, pp.50-61, 2014.
DOI : 10.1007/978-3-319-11382-1_6

N. Ramakrishnan and A. Grama, Data mining: from serendipity to science, Computer, vol.32, issue.8, pp.34-37, 1999.
DOI : 10.1109/2.781632

S. M. Weiss, N. Indurkhya, and T. Zhang, Fundamentals of Predictive Text Mining, Second Edition, ser. Texts in Computer Science, 2015.
DOI : 10.1007/978-1-4471-6750-1

J. Beel, B. Gipp, S. Langer, and C. Breitinger, Research-paper recommender systems: a literature survey, International Journal on Digital Libraries, vol.21, issue.3, pp.305-338, 2016.
DOI : 10.1007/s11257-011-9097-5

D. M. Blei, A. Y. Ng, and M. I. Jordan, Latent dirichlet allocation, Journal of Machine Learning Research, vol.3, pp.993-1022, 2003.

L. F. Klein, J. Eisenstein, and I. Sun, Exploratory Thematic Analysis for Digitized Archival Collections, Digital Scholarship in the Humanities, pp.130-141, 2015.
DOI : 10.1093/llc/fqv052

URL : https://academic.oup.com/dsh/article-pdf/30/suppl_1/i130/1042861/fqv052.pdf

J. He, Y. Huang, C. Liu, J. Shen, Y. Jia et al., Text Network Exploration via Heterogeneous Web of Topics, 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), pp.99-106, 2016.
DOI : 10.1109/ICDMW.2016.0022

T. M. Le and H. W. Lauw, Semantic visualization with neighborhood graph regularization, J. Artif. Intell. Res. (JAIR), vol.55, pp.1091-1133, 2016.

B. Gretarsson, J. O-'donovan, S. Bostandjiev, T. Höllerer, A. U. Asuncion et al., TopicNets, ACM Transactions on Intelligent Systems and Technology, vol.3, issue.2, pp.1-2326, 2012.
DOI : 10.1145/2089094.2089099

Q. He, B. Chen, J. Pei, B. Qiu, P. Mitra et al., Detecting topic evolution in scientific literature, Proceeding of the 18th ACM conference on Information and knowledge management, CIKM '09, pp.957-966, 2009.
DOI : 10.1145/1645953.1646076

E. C. Alexander, J. Kohlmann, R. Valenza, M. Witmore, and M. Gleicher, Serendip: Topic model-driven visual exploration of text corpora, 2014 IEEE Conference on Visual Analytics Science and Technology (VAST), pp.173-182, 2014.
DOI : 10.1109/VAST.2014.7042493

R. Collobert, J. Weston, L. Bottou, M. Karlen, K. Kavukcuoglu et al., Natural language processing (almost) from scratch, Journal of Machine Learning Research, vol.12, pp.2493-2537, 2011.

T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean, Distributed representations of words and phrases and their compositionality, Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013 Proceedings of a meeting held, pp.3111-3119, 2013.

J. Pennington, R. Socher, and C. D. Manning, Glove: Global Vectors for Word Representation, Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.1532-1543, 2014.
DOI : 10.3115/v1/D14-1162

P. Bojanowski, E. Grave, A. Joulin, and T. Mikolov, Enriching word vectors with subword information, 2016.

Y. Shen, X. He, J. Gao, L. Deng, and G. Mesnil, Learning semantic representations using convolutional neural networks for web search, Proceedings of the 23rd International Conference on World Wide Web, WWW '14 Companion, pp.373-374, 2014.
DOI : 10.1145/1076034.1076115

R. Kiros, Y. Zhu, R. Salakhutdinov, R. S. Zemel, R. Urtasun et al., Skip-thought vectors, Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, pp.3294-3302, 2015.

M. Pagliardini, P. Gupta, and M. Jaggi, Unsupervised learning of sentence embeddings using compositional n-gram features, 1703.

Q. V. Le and T. Mikolov, Distributed representations of sentences and documents, Proceedings of the 31th International Conference on Machine Learning Conference Proceedings, pp.21-26, 2014.

P. Huang, X. He, J. Gao, L. Deng, A. Acero et al., Learning deep structured semantic models for web search using clickthrough data, Proceedings of the 22nd ACM international conference on Conference on information & knowledge management, CIKM '13, pp.2333-2338, 2013.
DOI : 10.1145/2505515.2505665

URL : http://research.microsoft.com/en-us/um/people/jfgao/paper/2013/cikm2013_DSSM_fullversion.pdf

T. K. Landauer, P. W. Foltz, and D. Laham, An introduction to latent semantic analysis, Discourse processes, pp.259-284, 1998.
DOI : 10.1080/01638539809545030

URL : http://www.cs.ucla.edu/~rosen/161/hw/intro_to_LSA.pdf

C. F. Van-loan, Generalizing the Singular Value Decomposition, SIAM Journal on Numerical Analysis, vol.13, issue.1, pp.76-83, 1976.
DOI : 10.1137/0713009

A. Abrizah, A. N. Zainab, K. Kiran, and R. G. Raj, LIS journals scientific impact and subject categorization: a comparison between Web of Science and Scopus, Scientometrics, vol.86, issue.1, pp.721-740, 2013.
DOI : 10.1002/(SICI)1097-0266(199903)20:3<279::AID-SMJ33>3.0.CO;2-2

A. Severyn and A. Moschitti, Modeling relational information in question-answer pairs with convolutional neural networks, 2016.

K. Tymoshenko, D. Bonadiman, and A. Moschitti, Convolutional Neural Networks vs. Convolution Kernels: Feature Engineering for Answer Sentence Reranking, Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp.1268-1278, 2016.
DOI : 10.18653/v1/N16-1152

L. Chen, R. Bao, Y. Li, K. Zhang, Y. An et al., An interactive information-retrieval method based on active learning, Journal of Engineering Science & Technology Review, vol.10, issue.3, 2017.
DOI : 10.25103/jestr.103.01

URL : https://doi.org/10.25103/jestr.103.01

Q. V. Le and T. Mikolov, Distributed representations of sentences and documents, Proceedings of the 31th International Conference on Machine Learning Conference Proceedings, pp.21-26, 2014.

E. Agirre, C. Banea, D. Cer, M. Diab, A. Gonzalez-agirre et al., SemEval-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation, Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), pp.497-511, 2016.
DOI : 10.18653/v1/S16-1081

N. Halko, P. Martinsson, and J. A. Tropp, Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions, SIAM Review, vol.53, issue.2, pp.217-288, 2011.
DOI : 10.1137/090771806

H. T. Al-natsheh, L. Martinet, F. Muhlenbach, and D. A. Zighed, Udl at semeval-2017 task 1: Semantic textual similarity estimation of english sentence pairs using regression model over pairwise features, Proceedings of the 11th International Workshop on Semantic Evaluation, pp.115-119, 2017.

F. Wilcoxon, Individual Comparisons by Ranking Methods, Biometrics Bulletin, vol.1, issue.6, pp.80-83, 1945.
DOI : 10.2307/3001968

J. Cohen, A Coefficient of Agreement for Nominal Scales, Educational and Psychological Measurement, vol.20, issue.1, pp.37-46, 1960.
DOI : 10.1037/h0044251

M. Tlauka, Orientation dependent mental representations following real-world navigation, Scandinavian Journal of Psychology, vol.28, issue.3, pp.171-176, 2006.
DOI : 10.1037/0278-7393.25.3.664

N. Sadato, T. Okada, M. Honda, K. Matsuki, M. Yoshida et al., Cross-modal integration and plastic changes revealed by lip movement, random-dot motion and sign languages in the hearing and deaf, Cerebral Cortex, vol.15, issue.8, pp.1113-1122, 2005.
DOI : 10.1093/cercor/bhh210