Information retrieval and recommendation systems
The primary aim of this research line is focused on improving the definition and development of mechanism and models applied…
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Data Science and Big Data Area
Data Science is the discipline that gathers all the work of analysis on data sets that requires a considerable amount of skills in programming, engineering and software management, as well as extensive knowledge in Mathematics, Statistics and Computer Science.
Problem solving through Data Science involves a series of stages such as: understanding the data, extracting its properties, modeling and analyzing the problem, presenting results, and developing software to exploit the knowledge extracted. Data Science provides the tools to deal with and benefit from Big Data.
Big Data is creating new opportunities in all the aspects of technology by leveraging its most valuable asset: information. Big Data Technologies help improve efficiency, quality, and the personalized products and services offered by organizations. In scientific terms, Big Data Analysis opens new research horizons with potentially more promising results and deeper revelations than before. In many cases, Big Data analysis integrates structured and unstructured data with real-time responses, opening new paths to innovation and development.
Research Lines
Research lines in the area of Data Science and Big Data.
Natural Language Processing and Social Network Analysis
The knowledge is one of the outcomes of the humankind, and it is encoded in natural language, which is the…
More infoarrow_forwardData Processing
In recent years there has been an immense growth in data, leading to the Big Data. This requires large computing…
More infoarrow_forwardDescriptive Data Mining
Descriptive data mining techniques are aimed at describing the data or the phenomenon underlying the data, and are generally applied…
More infoarrow_forwardMachine Learning and image processing
Machine Learning is the branch of artificial intelligence whose objective is the development of techniques that allow computers to learn…
More infoarrow_forwardRobust Machine Learning
As Machine Learning (ML) is applied to increasingly sensitive tasks, and applied to increasingly noisy data, it has become important…
More infoarrow_forwardMachine Learning in singular and non-standard problems
In recent years, new problems and paradigms have appeared in Machine Learning, which, in some way, do not fit into…
More infoarrow_forwardExplicability, Privacy and Equity in Machine Learning
Artificial Intelligence (AI) offers increasingly precise algorithms that make it possible to analyse all kinds of data or signals, such…
More infoarrow_forwardDeep Learning
The complexity of the information with which we currently operate, with large sets of attributes describing each of the data…
More infoarrow_forwardBlockchain and Data Protection
Blockchain is the underlying technology of all the crypto currencies that have been emerging in the first decades of the…
More infoarrow_forwardFederated Learning and Privacy
Federated Learning is a distributed learning paradigm which arises from both, the increasing awareness of data privacy and the growing…
More infoarrow_forwardReal-time data analysis
The process of obtaining models from data, either for prediction or monitoring, is often difficult or impossible to perform with…
More infoarrow_forwardTime series analysis and prediction
A time series is a set of data relating to the measurement of a magnitude (scalar or vector) ordered in…
More infoarrow_forwardBig Data
Data Science and Big Data analytics have become a growing demand nowadays. These are complementary areas that aim at extracting…
More infoarrow_forwardArea Coordinators
María José del Jesus Díaz, Universidad de Jaén
Sebastián Ventura, Universidad de Córdoba
Salvador García, Universidad de Granada