Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in

This work presents an adaptive hypermedia proposal that focuses on the students' lexicon. An adequate lexicon knowledge affects dramatically in the learning processes in which the students are involved. In general, students manage a lexicon level that allows them to communicate. However, this is not enough for understanding specialized texts covering specific topics. Our proposal takes into account the interconnecting structures present in the lexicon associated to a student profile. More specifically, we propose a set of rules that, based on the student profile, facilitate the selection of the lexicon. We also provide a description of the different instances involved in the complete process.

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