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Entropy Guided Transformation Learning: Algorithms and Applications

  • Cícero Nogueira dos Santos
  • Ruy Luiz Milidiú

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Entropy Guided Transformation Learning: Algorithms

    1. Front Matter
      Pages 1-1
    2. Cícero Nogueira dos Santos, Ruy Luiz Milidiú
      Pages 3-8
    3. Cícero Nogueira dos Santos, Ruy Luiz Milidiú
      Pages 9-21
    4. Cícero Nogueira dos Santos, Ruy Luiz Milidiú
      Pages 23-28
  3. Entropy Guided Transformation Learing: Applications

    1. Front Matter
      Pages 29-29
    2. Cícero Nogueira dos Santos, Ruy Luiz Milidiú
      Pages 31-34
    3. Cícero Nogueira dos Santos, Ruy Luiz Milidiú
      Pages 35-41
    4. Cícero Nogueira dos Santos, Ruy Luiz Milidiú
      Pages 43-49
    5. Cícero Nogueira dos Santos, Ruy Luiz Milidiú
      Pages 51-58
    6. Cícero Nogueira dos Santos, Ruy Luiz Milidiú
      Pages 59-69
    7. Cícero Nogueira dos Santos, Ruy Luiz Milidiú
      Pages 71-73
  4. Back Matter
    Pages 75-78

About this book

Introduction

Entropy Guided Transformation Learning: Algorithms and Applications (ETL) presents a machine learning algorithm for classification tasks. ETL generalizes Transformation Based Learning (TBL) by solving the TBL bottleneck: the construction of good template sets. ETL automatically generates templates using Decision Tree decomposition.

The authors describe ETL Committee, an ensemble method that uses ETL as the base learner. Experimental results show that ETL Committee improves the effectiveness of ETL classifiers. The application of ETL is presented to four Natural Language Processing (NLP) tasks: part-of-speech tagging, phrase chunking, named entity recognition and semantic role labeling. Extensive experimental results demonstrate that ETL is an effective way to learn accurate transformation rules, and shows better results than TBL with handcrafted templates for the four tasks. By avoiding the use of handcrafted templates, ETL enables the use of transformation rules to a greater range of tasks.

Suitable for both advanced undergraduate and graduate courses, Entropy Guided Transformation Learning: Algorithms and Applications provides a comprehensive introduction to ETL and its NLP applications.

Keywords

Entropy Guided Transformation Learning Named Entity Recognition Part-of-speech Tagging Semantic Role Labeling Transformation Based Learning

Authors and affiliations

  • Cícero Nogueira dos Santos
    • 1
  • Ruy Luiz Milidiú
    • 2
  1. 1.Universidade de FortalezaFortalezaBrazil
  2. 2.Departamento de InformáticaPontifícia Universidade Católica do RioRio de JaneiroBrazil

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-2978-3
  • Copyright Information The Author(s) 2012
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-4471-2977-6
  • Online ISBN 978-1-4471-2978-3
  • Series Print ISSN 2191-5768
  • Series Online ISSN 2191-5776
  • Buy this book on publisher's site