E. Agirre, E. Alfonseca, K. Hall, J. Kravalova, M. Pa¸scapa¸sca et al., A study on similarity and relatedness using distributional and WordNet-based approaches, Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics on, NAACL '09, pp.19-27, 2009.
DOI : 10.3115/1620754.1620758

E. Alfonseca, K. Hall, and S. Hartmann, Large-scale computation of distributional similarities for queries, Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers on, NAACL '09, pp.29-32, 2009.
DOI : 10.3115/1620853.1620863

E. H. Anguiano and P. Denis, FreDist: Automatic construction of distributional thesauri for French, Actes de la 18 e conférence sur le traitement automatique des langues naturelles ? TALN, pp.119-124, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00602004

T. Baldwin, C. Bannard, T. Tanaka, and D. Widdows, An empirical model of multiword expression decomposability, Proceedings of the ACL 2003 workshop on Multiword expressions analysis, acquisition and treatment -, pp.89-96, 2003.
DOI : 10.3115/1119282.1119294

M. Baroni, G. Dinu, and G. Kruszewski, Don't count, predict! a systematic comparison of contextcounting vs. context-predicting semantic vectors, Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, pp.238-247, 2014.

M. Baroni and A. Lenci, Distributional Memory: A General Framework for Corpus-Based Semantics, Computational Linguistics, vol.37, issue.1, pp.673-721, 2010.
DOI : 10.1162/coli.08-032-R1-06-96

M. Baroni and A. Lenci, How we BLESSed distributional semantic evaluation, Proceedings of the GEMS 2011 Workshop on GEometrical Models of Natural Language Semantics, pp.1-10, 2011.

M. Baroni and R. Zamparelli, Nouns are vectors, adjectives are matrices: Representing adjectivenoun constructions in semantic space, Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pp.1183-1193, 2010.

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

G. Boleda and K. Erk, Distributional semantic features as semantic primitives ? or not, AAAI Spring Symposium on Knowledge Representation and Reasoning

E. Bruni, N. Tran, and M. Baroni, Multimodal Distributional Semantics, Journal of Artificial Intelligence Research (JAIR), vol.49, pp.1-47, 2014.

A. Budanitsky and G. Hirst, Evaluating WordNet-based Measures of Lexical Semantic Relatedness, Computational Linguistics, vol.17, issue.1, pp.13-47, 2006.
DOI : 10.1016/S0022-5371(79)90604-2

J. Bullinaria and J. P. Levy, Extracting semantic representations from word co-occurrence statistics: A computational study, Behavior Research Methods, vol.35, issue.6, pp.510-526, 2007.
DOI : 10.3758/BF03193020

J. C. Cheung and G. Penn, Probabilistic Domain Modelling With Contextualized Distributional Semantic Vectors, Association for Computational Linguistics (ACL), pp.392-401, 2013.

V. Claveau and E. Kijak, Thésaurus distributionnels pour la recherche d'information et viceversa, Actes de la 13 e Conférence en Recherche d'Information et Applications (CORIA), 2015.

R. Collobert and J. Weston, A unified architecture for natural language processing, Proceedings of the 25th international conference on Machine learning, ICML '08, pp.160-167, 2008.
DOI : 10.1145/1390156.1390177

J. R. Curran, From distributional to semantic similarity, 2004.

J. R. Curran and M. Moens, Improvements in automatic thesaurus extraction, Proceedings of the ACL-02 workshop on Unsupervised lexical acquisition -, pp.59-66, 2002.
DOI : 10.3115/1118627.1118635

K. Erk, Towards a semantics for distributional representations, Proceedings of the 10th International Conference on Computational Semantics, 2013.

C. Fabre, N. Hathout, L. Ho-dac, F. Morlane-hondère, P. Muller et al., Présentation de l'atelier SemDis 2014: sémantique distributionnelle pour la substitution lexicale et l'exploration de corpus spécialisés, Actes de la conférence Traitement Automatique du Langage Naturel, pp.196-205, 2014.

O. Ferret, Identifying Bad Semantic Neighbors for Improving Distributional Thesauri, 51st Annual Meeting of the Association for Computational Linguistics?ACL 2013, pp.561-571, 2013.
DOI : 10.1007/978-3-319-08043-7_8

L. Finkelstein, E. Gabrilovich, Y. Matias, E. Rivlin, Z. Solan et al., Placing search in context, Proceedings of the tenth international conference on World Wide Web , WWW '01, pp.116-131, 2002.
DOI : 10.1145/371920.372094

E. Grefenstette, Towards a formal distributional semantics: Simulating logical calculi with tensors, Proceedings of the Second Joint Conference on Lexical and Computational Semantics, pp.1-10, 2013.

G. Grefenstette, Explorations in Automatic Thesaurus Discovery, 1994.
DOI : 10.1007/978-1-4615-2710-7

E. Guevara, Computing semantic compositionality in distributional semantics, Proceedings of the Ninth International Conference on Computational Semantics, pp.135-144, 2011.

A. Gupta, G. Boleda, M. Baroni, and S. Padó, Mapping conceptual features to referential properties, Conference on Empirical Methods in Natural Language Processing, p.2015

B. Habert and P. Zweigenbaum, Contextual acquisition of information categories The Legacy of Zellig Harris: Language and information into the 21st century, pp.139-159, 2002.

Z. S. Harris, Distributional structure, pp.146-162, 1954.

Z. S. Harris, A Theory of Language and Information: A Mathematical Approach, 1991.

A. Herbelot and M. Ganesalingam, Measuring semantic content in distributional vectors, Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, pp.440-445, 2013.

F. Hill, R. Reichart, and A. Korhonen, SimLex-999: Evaluating Semantic Models With (Genuine) Similarity Estimation, Computational Linguistics, vol.41, issue.4
DOI : 10.1037/0033-295X.84.4.327

D. Kiela and S. Clark, A Systematic Study of Semantic Vector Space Model Parameters, Proceedings of the 2nd Workshop on Continuous Vector Space Models and their Compositionality (CVSC), pp.21-30, 2014.
DOI : 10.3115/v1/W14-1503

A. Koller, Top-down questions for distributional semantics, Presentation at the Workshop on formal and distributional semantics

T. K. Landauer and S. T. Dumais, A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge., Psychological Review, vol.104, issue.2, p.211, 1997.
DOI : 10.1037/0033-295X.104.2.211

G. Lapesa and S. Evert, A large scale evaluation of distributional semantic models: Parameters, interactions and model selection, Transactions of the Association for Computational Linguistics, vol.2, pp.531-545, 2014.

A. Lenci, Distributional semantics in linguistic and cognitive research " , From context to meaning: Distributional models of the lexicon in linguistics and cognitive science, special issue of the, Italian Journal of Linguistics, vol.20, issue.1, pp.1-31, 2008.

A. Lenci, G. *. Benotto, and . Sem, Identifying hypernyms in distributional semantic spaces, The First Joint Conference on Lexical and Computational Semantics, pp.75-79, 2012.

I. Leviant and R. Reichart, Judgment Language Matters: Multilingual Vector Space Models for Judgment Language Aware Lexical Semantics, 2015.

O. Levy and Y. Goldberg, Linguistic Regularities in Sparse and Explicit Word Representations, Proceedings of the Eighteenth Conference on Computational Natural Language Learning, pp.171-180, 2014.
DOI : 10.3115/v1/W14-1618

O. Levy, Y. Goldberg, and I. Dagan, Improving Distributional Similarity with Lessons Learned from Word Embeddings, Transactions of the ACL, vol.3, pp.211-225, 2015.

C. Lund and K. Burgess, Modelling parsing constraints with high-dimensional context space, Language and cognitive processes, vol.12, pp.2-3, 1997.

M. Marelli, L. Bentivogli, M. Baroni, R. Bernardi, S. Menini et al., SemEval-2014 Task 1: Evaluation of Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment, Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), pp.1-8, 2014.
DOI : 10.3115/v1/S14-2001

D. Mccarthy, R. Koeling, J. Weeds, and J. Carroll, Unsupervised Acquisition of Predominant Word Senses, Computational Linguistics, vol.13, issue.02, pp.553-590, 2007.
DOI : 10.1017/S135132490200298X

D. Mccarthy and R. Navigli, SemEval-2007 task 10, Proceedings of the 4th International Workshop on Semantic Evaluations, SemEval '07, pp.48-53, 2007.
DOI : 10.3115/1621474.1621483

T. Mikolov, K. Chen, G. Corrado, and J. Dean, Efficient Estimation of Word Representations in Vector Space, Proceedings of Workshop at ICLR 2013, pp.1-12, 2013.

T. Mikolov, W. Yih, and G. Zweig, Linguistic Regularities in Continuous Space Word Representations, Proceedings of NAACL-HLT 2013, pp.746-751, 2013.

J. Mitchell and M. Lapata, Composition in Distributional Models of Semantics, Cognitive Science, vol.14, issue.3, pp.1388-1439, 2010.
DOI : 10.1111/j.1551-6709.2010.01106.x

J. Morris and G. Hirst, Non-classical lexical semantic relations, Proceedings of the HLT-NAACL Workshop on Computational Lexical Semantics, CLS '04, pp.46-51, 2004.
DOI : 10.3115/1596431.1596438

P. Muller, C. Fabre, and C. Adam, Predicting the relevance of distributional semantic similarity with contextual information, Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp.479-488, 2014.
DOI : 10.3115/v1/P14-1045

URL : https://hal.archives-ouvertes.fr/hal-01056292

A. Nazarenko, P. Zweigenbaum, B. Habert, and J. Bouaud, Corpus-based extension of a terminological semantic lexicon, Recent Advances in Computational Terminology, pp.327-351, 2001.
DOI : 10.1075/nlp.2.17naz

URL : https://hal.archives-ouvertes.fr/hal-00619266

S. Padó and M. Lapata, Dependency-Based Construction of Semantic Space Models, Computational Linguistics, vol.24, issue.1, pp.161-199, 2007.
DOI : 10.1017/S135132490200298X

M. Padró, M. Idiart, C. Ramisch, and A. Villavicencio, Nothing like Good Old Frequency: Studying Context Filters for Distributional Thesauri, Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.419-424, 2014.
DOI : 10.3115/v1/D14-1047

Y. Peirsman and D. Geeraerts, Predicting strong associations on the basis of corpus data, Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics on, EACL '09, pp.648-656, 2009.
DOI : 10.3115/1609067.1609139

Y. Peirsman, K. Heylen, and D. Speelman, Finding semantically related words in Dutch Cooccurrences versus syntactic contexts, Proceedings of the 2007 Workshop on Contextual Information in Semantic Space Models: Beyond Words and Doc-uments, pp.9-16, 2007.

M. Sadrzadeh and E. Grefenstette, A Compositional Distributional Semantics, Two Concrete Constructions, and Some Experimental Evaluations, Quantum Interaction, pp.35-47, 2011.
DOI : 10.1007/978-3-642-24971-6_5

M. Sahlgren, The Word-Space Model, 2006.

M. Sahlgren, The distributional hypothesis, Italian Journal of Linguistics, vol.20, issue.1, pp.33-54, 2008.

G. Salton, A. Wong, and C. Yang, A vector space model for automatic indexing, Communications of the ACM, vol.18, issue.11, pp.613-620, 1975.
DOI : 10.1145/361219.361220

E. Santus, A. Lenci, Q. Lu, and S. Schulte-im-walde, Chasing Hypernyms in Vector Spaces with Entropy, Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers, pp.38-42, 2014.
DOI : 10.3115/v1/E14-4008

E. Santus, F. Yung, A. Lenci, and C. Huang, EVALution 1.0: an Evolving Semantic Dataset for Training and Evaluation of Distributional Semantic Models, Proceedings of the 4th Workshop on Linked Data in Linguistics: Resources and Applications, pp.64-69, 2015.
DOI : 10.18653/v1/W15-4208

T. Pham, N. Lazaridou, A. Baroni, and M. , A Multitask Objective to Inject Lexical Contrast into Distributional Semantics, Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pp.21-26, 2015.
DOI : 10.3115/v1/P15-2004

P. D. Turney, Similarity of Semantic Relations, Computational Linguistics, vol.17, issue.1, pp.379-416, 2006.
DOI : 10.1162/153244303322533205

P. D. Turney, Distributional semantics beyond words: Supervised learning of analogy and paraphrase, Transactions of the Association for Computational Linguistics (TACL), vol.1, pp.353-366, 2013.

P. D. Turney and P. Pantel, From frequency to meaning: Vector space models of semantics, Journal of artificial intelligence research, vol.37, issue.1, pp.141-188, 2010.

T. Van-de-cruys, A comparison of bag of words and syntax-based approaches for word categorization, Proceedings of the ESSLLI Workshop on Distributional Lexical Semantics, pp.47-54, 2008.

T. Van-de-cruys, A non-negative tensor factorization model for selectional preference induction, Natural Language Engineering, vol.39, issue.04, pp.417-437, 2010.
DOI : 10.1002/(SICI)1099-128X(199709/10)11:5<393::AID-CEM483>3.0.CO;2-L

URL : https://hal.archives-ouvertes.fr/inria-00546045

L. Van-der-plas and J. Tiedemann, Finding synonyms using automatic word alignment and measures of distributional similarity, Proceedings of the COLING/ACL on Main conference poster sessions -, pp.866-873, 2006.
DOI : 10.3115/1273073.1273184

L. Van-der-plas, J. Tiedemann, and J. Manguin, Synonym Acquisition across Domains and Languages, Advances in Distributed Agent-Based Retrieval Tools, pp.41-57, 2011.
DOI : 10.1007/978-3-642-21384-7_4

A. Zarcone, S. Padó, and A. Lenci, Same same but different: Type and typicality in a distributional model of complement coercion, Proceedings of the NetWordS Final Conference on Word Knowledge and Word Usage, pp.91-94, 2015.