Data-Driven Recommender Systems: Sequences of recommendations

Jérémie Mary 1, 2
1 SEQUEL - Sequential Learning
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : This document is about some scalable and reliable methods for recommender systems from a machine learner point of view. In particular it adresses some difficulties from the non stationary case.
Document type :
Habilitation à diriger des recherches
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Jérémie Mary. Data-Driven Recommender Systems: Sequences of recommendations. Artificial Intelligence [cs.AI]. Université de Lille 3, 2015. ⟨tel-01374729⟩

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