- Data mining: It is the process of extracting hidden nontrivial information and patterns from the data, addressing the solution of prediction, classificaiton and segmentation problems.
- Applied visualization techniques: Multidimensional data visualization, and 3D modeling and virtual reality for the diffusion of the historical-artistic and archaeological heritage.
- Ensemble construction: Designing new algorithms for construction strong classifiers from the combination of a set of weak classifiers.
- Bioinformatics: Application of data mining and for solving problems such as sequence aligning and gene prediction.
- Instance and feature selection: Reduce the number of instances and characteristics of a data set to speed up further processing without information lost.
- Data Mining applied to Software Engineering: Reduction of software maintenance costs by improving the quality of software processes and products through the application of data mining.
- Big Data: Parallelization of data mining algorithms to adapt them to processing large volumes of data.
