Data Mining Research Team

Data Mining Research Team, as well as Knowledge Discovery in Data, represents a scientific subject matter that integrates conceptions coming from information theory, discrete mathematics, statistics, machine learning, and pattern recognition, together with the data visualization, databases, Web and parallel programming, among others. This varied fusion of subjects has been motivated by the huge increase of data in all spheres of human life and the economic and scientific need of extracting valuable information from data available in different means.

When we talk about “data” we are talking about all structured, semi-structured or non-structured data, like the information comprised in databases and data warehouse, as well as images, signals, spatial and temporal data, and textual information stored in a variety of means. Moreover, when we talk about “databases” we are considering static and dynamic data.

The interests of the Data Mining Department cover from the methodological aspects of the process of knowledge discovery, the development and improvement of the existing paradigms, to their application in different problems arising in all spheres of our society. Among the interests of the Department, the following topics are included:

Data mining algorithms (such as classification, clustering, frequent pattern and association analysis).
Mining on different data types (such as texts, graphs, sequences, spatial and temporal data).
Social Network Analysis, Text and Web mining, opinion mining, natural language processing and computational linguistic.
Data mining algorithms using parallel and distributed programming, and reconfigurable architectures for scientific computing techniques.

Members

Head of Data Mining Research Team:

PhD. Andrés Gago Alonso

Researchers: