M. Almasri, C. Berrut, and J. Chevallet, A Comparison of Deep Learning Based Query Expansion with Pseudo-Relevance Feedback and Mutual Information, European Conference on IR Research, pp.709-715, 2016.
DOI : 10.1007/978-3-642-37256-8_31

S. Deerwester, S. T. Dumais, G. W. Furnas, T. K. Landauer, and R. Harshman, Indexing by latent semantic analysis, Journal of the American Society for Information Science, vol.41, issue.6, pp.41391-407, 1990.
DOI : 10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9

D. Ganguly, D. Roy, M. Mitra, and G. J. Jones, Word Embedding based Generalized Language Model for Information Retrieval, Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '15, pp.795-798, 2015.
DOI : 10.1145/2766462.2767780

Y. Goldberg and O. Levy, word2vec explained: deriving mikolov et al.'s negative-sampling word-embedding method. CoRR, abs/1402, 2014.

Y. Kim, Convolutional neural networks for sentence classification. CoRR, abs, 1408.

M. Koolen, T. Bogers, M. Gäde, M. A. Hall, H. C. Huurdeman et al., Overview of the CLEF 2015 Social Book Search Lab, Conference and Labs of the Evaluation Forum, CLEF'15, pp.545-564, 2015.
DOI : 10.1007/978-3-319-24027-5_51

T. Mikolov, K. Chen, G. Corrado, and J. Dean, Efficient estimation of word representations in vector space, 1301.

E. Nalisnick, B. Mitra, N. Craswell, and R. Caruana, Improving Document Ranking with Dual Word Embeddings, Proceedings of the 25th International Conference Companion on World Wide Web , WWW '16 Companion, pp.83-84, 2016.
DOI : 10.1145/2872518.2889361

I. Ounis, G. Amati, V. Plachouras, B. He, C. Macdonald et al., Terrier: A High Performance and Scalable Information Retrieval Platform, SIGIR'06 Workshop on Open Source Information Retrieval, 2006.

D. Widdows, Geometry and Meaning. Center for the Study of Language and Information/SRI, 2004.