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We describe here an experimental framework and the results obtained onmicroblogs retrieval. We study the contribution one popular approach, i.e.,words embeddings, and investigate the impact of the training set on the learnedembedding. We focus on query expansion for the retrieval of tweets on the CLEFCMC 2016 corpus. Our results show that using embeddings trained on a corpus inthe same domain as the indexed documents did not necessarily lead to betterretrieval results.

Quels corpus d'entra\^inement pour l'expansion de requ\^etes par plongement de mots : application \`a la recherche de microblogs culturels