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

Format:

Book

Author/Creator:

Santos, Cícero Nogueira dos, author.

Milidiu, Ruy Luiz, author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

SpringerBriefs in computer science 2191-5768

SpringerBriefs in Computer Science, 2191-5768

Language:

English

Subjects (All):

Pattern perception.

Natural language processing (Computer science).

Computational linguistics.

Pattern Recognition.

Natural Language Processing (NLP).

Computational Linguistics.

Local Subjects:

Pattern Recognition.

Natural Language Processing (NLP).

Computational Linguistics.

Physical Description:

1 online resource (XIII, 78 pages) : 10 illustrations.

Edition:

First edition 2012.

Contained In:

Springer eBooks

Place of Publication:

London : Springer London : Imprint: Springer, 2012.

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.

Other Format:

Printed edition:

ISBN:

978-1-4471-2978-3

9781447129783

Access Restriction:

Restricted for use by site license.