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Selecting a Feature Set to Summarize Texts in Brazilian Portuguese

  • Daniel Saraiva Leite
  • Lucia Helena Machado Rino
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4140)

Abstract

This paper presents a novel approach to combining features for training an automatic extractive summarizer of texts written in Brazilian Portuguese. The approach aims at both diminishing the effort of classifying features that are representative for Automatic Summarization and providing more informativeness for the summarizer to decide which text spans to include in an extract. Finding a balanced set of features is explored through WEKA. We discuss several ways of modifying the feature set and show how automatic feature selection may be useful for customizing the summarizer.

Keywords

Feature Selection Feature Subset Source Text Sentence Length Proper Noun 
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 2006

Authors and Affiliations

  • Daniel Saraiva Leite
    • 1
  • Lucia Helena Machado Rino
    • 1
  1. 1.Departamento de ComputaçãoUFSCar Núcleo Interinstitucional de Lingüística ComputacionalSão CarlosBrazil

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