B. Rjab, A. , M. Kharoune, Z. Miklos, and E. A. Martin, Characterization of experts in crowdsourcing platforms, The 4th International Conference on Belief Functions, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01372142

B. Rjab, A. , M. Kharoune, Z. Miklos, A. Martin et al., Caractérisation d'experts dans les plate-formes de crowdsourcing, 24 ème Conférence sur la Logique Floue et ses Applications, 2015.

A. P. Dawid, A. M. Et, and . Skene, Maximum Likelihood Estimation of Observer Error-Rates Using the EM Algorithm, Applied Statistics, vol.28, issue.1, pp.20-28, 1979.
DOI : 10.2307/2346806

A. P. Dempster, Upper and lower probabilities induced by a multivalued mapping. The annals of mathematical statistics, pp.325-339, 1967.

A. Essaid, A. Martin, G. Smits, and B. B. Yaghlane, A Distance-Based Decision in the Credal Level, Artificial Intelligence and Symbolic Computation -12th International Conference. Proceedings, pp.147-156, 2014.
DOI : 10.1007/978-3-319-13770-4_13
URL : https://hal.archives-ouvertes.fr/hal-01110349

J. Howe, The rise of crowdsourcing, pp.1-4, 2006.

P. Ipeirotis, Worker evaluation in crowdsourcing : Gold data or multiple workers ?, 2010.

P. G. Ipeirotis, F. Provost, and E. J. Wang, Machine-learning for spammer detection in crowd-sourcing, HCOMP '10 Proceedings of the ACM SIGKDD Workshop on Human Computation, 2010.

S. Jouili, Indexation de masses de documents graphiques : approches structurelles, 2011.
URL : https://hal.archives-ouvertes.fr/tel-00597711

A. Jousselme, D. Grenier, and E. É. Bossé, A new distance between two bodies of evidence, Information Fusion, vol.2, issue.2, pp.91-101, 2001.
DOI : 10.1016/S1566-2535(01)00026-4

J. Le, A. Edmonds, V. Hester, and E. L. Biewald, Ensuring quality in crowdsourced search relevance evaluation : The effects of training question distribution, Workshop on Crowdsourcing for Search Evaluation, 2010.

P. Philips, Enterprise crowdsourcing or : How i learned to stop worrying and trust the crowd, 2011.

V. C. Raykar, S. Et, and . Yu, Annotation models for crowdsourced ordinal data, Journal of Machine Learning Research, vol.13, 2012.

V. C. Raykar, S. Yu, L. H. Zhao, G. H. Valadez, C. Florin et al., Learning from crowds, Journal of Machine Learning Research, vol.11, pp.1297-1322, 2010.

G. Shafer, A mathematical theory of evidence, 1976.

P. Smets, The combination of evidence in the transferable belief model, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.12, issue.5, pp.447-458, 1990.
DOI : 10.1109/34.55104

P. Smyth, U. Fayyad, M. Burl, P. Perona, and E. P. Baldi, Inferring ground truth from subjective labelling of venus images, Advances in Neural Information Processing Systems, pp.1085-1092, 1995.