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Distributing Text Classification in Grid Environments

  • Catarina Silva
  • Bernardete Ribeiro
Part of the Studies in Computational Intelligence book series (SCI, volume 255)

Abstract

The previous chapters looked at several ways to improve the performance of support vector machines (SVMs) and relevance vector machines (RVMs) in text classification applications.

Most data mining problems are nowadays faced with two great challenges. First, the volume of digital data available is growing massively in almost all application areas. Second, state-of-the-art learning machines are becoming increasingly demanding in terms of computing power. This chapter establishes a high-performance distributed computing environment model where the learning techniques proposed in the previous chapters are efficiently deployed and tested in large scale corpora.

Keywords

Direct Acyclic Graph Schedule Scheme Testing Document Computing Node Grid Environment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Catarina Silva
    • Bernardete Ribeiro

      There are no affiliations available

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