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SpringerBriefs in Computer Science

Entropy Guided Transformation Learning: Algorithms and Applications

Authors: dos Santos, Cícero Nogueira, Milidiú, Ruy Luiz

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  • Detailed explanation of the Entropy Guided Transformation Learning algorithm
  • Detailed explanation of how to create ensembles of ETL classifiers
  • Explains how to apply ETL to four NLP problems
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About this book

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.

Table of contents (9 chapters)

Table of contents (9 chapters)

Buy this book

eBook $54.99
price for USA in USD (gross)
  • ISBN 978-1-4471-2978-3
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $69.99
price for USA in USD
  • ISBN 978-1-4471-2977-6
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Entropy Guided Transformation Learning: Algorithms and Applications
Authors
Series Title
SpringerBriefs in Computer Science
Copyright
2012
Publisher
Springer-Verlag London
Copyright Holder
The Author(s)
eBook ISBN
978-1-4471-2978-3
DOI
10.1007/978-1-4471-2978-3
Softcover ISBN
978-1-4471-2977-6
Series ISSN
2191-5768
Edition Number
1
Number of Pages
XIII, 78
Number of Illustrations
10 b/w illustrations
Topics

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