Metric-temporal databases are a new database model that combines metric spaces with temporal databases to process similarity queries within a time interval or snapshot. The Historical FHQT is a metric-temporal index which has shown to be competitive answering this type…

Data base management evolved during the sixties and seventies. The evolution period was protracted. Many driving forces impacted the evolution and it is the aim of this paper to analyze these driving forces (some technical and some political) and to…

This paper shows models of data description that incorporate uncertainty like models of data extension EER, IFO among others. These database modeling tools are compared with the pattern FuzzyEER proposed by us, which is an extension of the EER model…

The Web has became an obiquitous resource for distributed computing making it relevant to investigate new ways of providing efficient access to services available at dedicated sites. Efficiency is an ever-increasing demand which can be only satisfied with the development…

Minimization of query execution time is an important performance objective in distributed databases design. While total time is to be minimized for On Line Transaction Processing (OLTP) type queries, response time has to be minimized in Decision Support type queries.…

In a scene where stakeholders are geographically distributed, communication presents new challenges for research areas. Considering the characteristics of interpersonal communication and the virtual area where it is carried out, the importance of applying interdisciplinary approaches, such as Cognitive Engineering,…

In cases of extremely imbalanced dataset with high dimensions, standard machine learning techniques tend to be overwhelmed by the large classes. This paper rebalances skewed datasets by compressing the majority class. This approach combines Vector Quantization and Support Vector Machine…

Most search methods in metric spaces assume that the topology of the object collection is reasonably regular. However, there exist nested metric spaces, where objects in the collection can be grouped into clusters or subspaces, in such a way that…

This paper focuses on prediction and prevention of seismic risk through a system for decision making. Data Warehousing and OLAP operations are applied, together with, data mining tools like association rules, decision trees and clustering to predict aspects such as…

Resumen de la tesis del autor para obtener el grado de Magister en Redes de Datos de la Facultad de Informática de la UNLP, dirigida por Luis Armando Marrone.