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Prodotti recenti

Compositional Representation of Morphologically-Rich Input for Neural Machine Translation

Neural machine translation (NMT) models are typically trained with fixed-size input and output vocabularies, which creates an important bottleneck on their accuracy and generalization capability. As a solution, various studies proposed segmenting words into sub-word units and performing translation at...

Compositional Source Word Representations for Neural Machine Translation

Neural machine translation (NMT) mod- els are typically trained with fixed-size input and output vocabularies, which creates an important bottleneck on their accuracy and generalization capability. As a solution, various studies proposed segmenting words into sub-word units and performing translation&...

An Evaluation of Two Vocabulary Reduction Methods for Neural Machine Translation

Neural machine translation (NMT) models are conventionally trained with fixed-size vocabu- laries to control the computational complexity and the quality of the learned word represen- tations. This, however, limits the accuracy and the generalization capability of the models, especially for morph...

HeLiS: An Ontology for Supporting Healthy Lifestyles

The use of knowledge resources in the digital health domain is a trending activity significantly grown in the last decade. In this paper, we present HeLiS: an ontology aiming to provide in tandem a representation of both the food and physical activity domains and the defi...

Transfer of Innovation on Allergic Rhinitis and Asthma Multimorbidity in the Elderly (MACVIA-ARIA) - EIP on AHA Twinning Reference Site (GARD Research Demonstration Project)

The overarching goals of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) are to enable European citizens to lead healthy, active and independent lives whilst ageing. The EIP on AHA includes 74 Reference Sites. The aim of this study was to tra...

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