Knowledge discovery based on association rules
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Text and social media mining
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Building energy efficiency behaviour analysis
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Tendency analysis
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Sentiment analysis
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Anomaly detection by means of association rules
Bioinformatics
Description: Computational and Machine Learning application techniques for the analysis of massive data from Biomedicine and omic-sciences for the identification of biomarkers in the clinical and epidemiologic ambits.
- Computational and statistical analysis of data coming from high performance sequence technologies in Biomedicine
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Development and application of Machine Learning algorithms for the identification of biomarkers in genomics, transcriptomics and epigenomics.
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Fuzzy logic technologies for the ADN sequence analysis. Tecnologías de lógica difusa para el análisis de secuencias de ADN.
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Development of graph-based inference and prioritization algorithms.
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Text mining and semi-automatic detection of scientific literature.
Evolutionary computation and bio-inspired algorithms
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Artificial neural networks and Deep Learning
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Evolutionary algorithms and metaheuristics
Soft Computing in Data Mining
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Fuzzy association rule mining
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Representation and visualization models for crisp and fuzzy association rules.
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Information fusion by means of Data Mining techniques.
Internet of Things
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IoT and 4.0 industry.
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Ambient Intelligence.
Neural networks, neurocomputing and applications
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Deep Learning and Deep Reinforcement learning for sustainable development
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Time series prediction
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System identification and data-driven simulation
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Energy efficiency in buildings and smart grids
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Analysis of disinformation in social networks