Data mining from data streams
João Gama
Faculdade de Economia
Universidade do Porto

Abstract

The Data Mining community is faced to new challenges with the advent of sources producing continuous flow of data. These sources, known as data streams, are characterized by high-speed flow of huge amounts of data generated from non stationary distributions. In consequence, new learning techniques are needed to process streaming data in reasonable time and space. The goal of this talk is to present and discuss the research problems, issues and challenges in learning from data streams. We will discuss the current trends, challenges and open issues and future directions in learning from data streams.

Meeting SPE/CIM in Statistics and Data Mining