Manuel Ramos-Cabrer

TL;DR: Two contributions are presented that apply a semantic approach to improve recommendation results transparently to the users and propose a measure of practical expertise by exploiting the data available in any e-commerce recommender system - the consumption histories of the users.

TL;DR: This paper presents a many-valued logic that enables effective reasoning about uncertainty and inconsistency in requirements specifications, motivating the election of six truth values and the definition of a new implication connective.

TL;DR: Evaluation results are presented to prove the feasibility of the downsized semantic reasoning process in the DTV receivers, supported by a pre-selection of material driven by audience stereotypes in the head-end, and to assess the quality it achieves in comparison with previous ones.

TL;DR: This paper provides guidelines on how to support the proposed model over the technological basis of the modern Digital TV receivers (either domestic or mobile ones), and describes a sample scenario of personalized advertising.

TL;DR: A personalized e-commerce system that incentivizes the users to provide high-quality metadata for commercial products is proposed and a strategy that offers time-aware recommendations is explored by combining semantic reasoning about these annotations with item-specific time functions.