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Entropy Guided Transformation Learning: Algorithms and Applications [electronic resource] / by Cícero Nogueira dos Santos, Ruy Luiz Milidiú.

Author/Creator:
Santos, Cícero Nogueira dos author., Author,
Publication:
London : Springer London : Imprint: Springer, 2012.
Format/Description:
Book
1 online resource (XIII, 78 pages) : 10 illustrations
Edition:
1st ed. 2012.
Series:
Computer Science (Springer-11645)
SpringerBriefs in computer science 2191-5768
SpringerBriefs in Computer Science, 2191-5768
Contained In:
Springer eBooks
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Details

Subjects:
Pattern perception.
Natural language processing (Computer science).
Computational linguistics.
Local subjects:
Pattern Recognition. (search)
Natural Language Processing (NLP). (search)
Computational Linguistics. (search)
System Details:
text file PDF
Summary:
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.
Contents:
Preface
Acknowledgements
Acronyms
Part I Entropy Guided Transformation Learning: Algorithms
Introduction
Entropy Guided Transformation Learning
ETL Committee
Part II Entropy Guided Transformation Learning: Applications
General ETL Modeling for NLP Tasks
Part-of-Speech Tagging
Phrase Chunking
Named Entity Recognition
Semantic Role Labeling
Conclusions
Appendices.
Contributor:
Milidiu, Ruy Luiz, author., Author,
SpringerLink (Online service)
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Printed edition:
Printed edition:
ISBN:
978-1-4471-2978-3
9781447129783
Publisher Number:
10.1007/978-1-4471-2978-3 doi
Access Restriction:
Restricted for use by site license.