Dominique Longrée

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Neural network models describe semantic priming effects by way of mechanisms of activation of neurons coding for words that rely strongly on synaptic efficacies between pairs of neurons. Biologically inspired Hebbian learning defines efficacy values as a function of the activity of pre- and post-synaptic neurons only. It generates only pair associations(More)
4 RÉSUMÉ – Nous exposons ici différentes méthodes de classification automatique des textes littéraires et nous en comparons les performances, notamment en ce qui concerne leur aptitude à traduire les structurations génériques du corpus. Nous montrons qu'une approche topologique des textes, qui prend en compte leur linéarité fondamentale, c'est-à-dire(More)
This paper assesses the performance of three taggers (MBT, TnT and TreeTagger) when used for the morphosyntactic annotation of classical Latin texts. With this aim in view, we selected the training corpora,-as well as the samples used for tests-, from the texts of the LASLA database. The texts were chosen according to their ability to allow testing of the(More)
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