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"A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and exible methods of ...

"The amount of multidimensional data published on the semantic web (SW) is constantly increasing, due to initiatives such as Open Data and Open Government Data, among other ones. Models, languages, and tools, that allow ...

Post-translational modifications (PTMs) are fundamental traits of protein functionality and their study has been addressed using several approaches over the past years. However, screening methods developed to detect regu...

"Decision support systems for alert drug-drug interactions have been shown as valid strategy to reduce medical error. Even so the use of these systems has not been as expected, probably due to the lack of a suitable desi...

This work presents a systematic literature review on the application of Machine Learning algorithms in the development of effective movie recommender systems. With the increasing popularity of movie recommender systems i...

The purpose of this study is to introduce new design-criteria for next-generation hyperparameter optimization software. The criteria we propose include (1) define-by-run API that allows users to construct the parameter s...

Currently; grapheme offers a new opportunity to use in space technology and this is due to its amazing properties like conductivity, strength, flexibility and transparency which allows us to exploit new generation of ult...