In this presentation we will explain a new mathematical procedure for the automatic discovery of interesting research questions. We propose to classify research topics according to their relevance (how important is the topic) and nescience (a measure of our current understanding of that topic). Once topics have been classified according to their interestingness, we can identify new, previously unknown, research questions by the combination of already existing topics. The validity of the theory has been tested using a collection of scientific articles from the free encyclopedia Wikipedia. Other possible applications of the proposed methodology are discussed as well.

About Rafael García

Since February 2014, Rafael García works as a Research Engineer at IMDEA Networks. He first joined the team lead by Dr. Antonio Fernández Anta, and then moved on to work with Dr. Vincenzo Mancuso. His main areas of interest are Big Data, Data Science, Computational Science and Natural Computing.

Prior to his incorporation to IMDEA Networks, Rafael worked four years as Research Assistant for the Universidad de Córdoba (geographical information systems and remote sensing), three years as Research Assistant for Universidad Autónoma de Madrid and CERN (high energy physics), three years as R&D Manager for Andago Ingeniería (open source software development for e-government), and five years as entrepreneur (computational finance).

He obtained a B.Sc. degree in Computer Science from the Universidad de Córdoba (dissertation on Categorial data analysis and selection of log-linear models), a M.Sc. degree in Computational Sciences from the University of Amsterdam (dissertation on Morphological analysis of 3D branching structures), and a Diploma of Advanced Studies in Computer Science and Telecommunications from the Universidad Autónoma de Madrid (dissertation on Semantic grids and massively multiplayer online games).

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Este evento se impartirá en inglés