Francisco Serradilla

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In the context of e-learning recommender systems, we propose that the users with greater knowledge (for example, those who have obtained better results in various tests) have greater weight in the calculation of the recommendations than the users with less knowledge. To achieve this objective, we have designed some new equations in the nucleus of the(More)
The modeling of eco-driving behaviors is a key issue in the research of Intelligent Transportation Systems. Most efforts have been made regarding internal combustion vehicles, and few works have been reported in the field of electric vehicles. On the other hand, these behavior analyses are usually conducted through naturalistic driving researches that(More)
The capacity of recommender systems to make correct predictions is essentially determined by the quality and suitability of the collaborative filtering that implements them. The common memory-based metrics are Pearson correlation and cosine, however, their use is not always the most appropriate or sufficiently justified. In this paper, we analyze these two(More)
Recommender systems or recommendation systems are a subset of information filtering system that used to anticipate the 'evaluation' or 'preference' that user would feed to an item. In recent years E-commerce applications are widely using Recommender system. Generally the most popular E-commerce sites are probably music, news, books,(More)
The development of new-generation intelligent vehicle technologies will lead to a better level of road safety and CO<sub>2</sub> emission reductions. However, the weak point of all these systems is their need for comprehensive and reliable data. For traffic data acquisition, two sources are currently available: (1) infrastructure sensors and (2) floating(More)