Apress Windows 10 Release Sale

Entropy Guided Transformation Learning: Algorithms and Applications

By Cícero Nogueira dos Santos , Ruy Luiz Milidiú

  • eBook Price: $29.95
Buy eBook Buy Print Book

Entropy Guided Transformation Learning: Algorithms and Applications Cover Image

  • Add to Wishlist
  • ISBN13: 978-1-4471-2977-6
  • 91 Pages
  • User Level: Science
  • Publication Date: March 14, 2012
  • Available eBook Formats: PDF

Related Titles

  • Information Systems and Neuroscience
  • BPM - Driving Innovation in a Digital World
  • Data-Driven Process Discovery and Analysis
  • Physical Asset Management
  • Transactions on Large-Scale Data- and Knowledge-Centered Systems XVIII
  • UML @ Classroom
  • AIDA-CMK: Multi-Algorithm Optimization Kernel Applied to Analog IC Sizing
  • Computational Color Imaging
  • Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines
  • Non-Linear Finite Element Analysis in Structural Mechanics
Full Description
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

Table of Contents

  1. Preface.
  2. Acknowledgements.
  3. Acronyms.
  4. Part I Entropy Guided Transformation Learning: Algorithms.
  5. Introduction.
  6. Entropy Guided Transformation Learning.
  7. ETL Committee.
  8. Part II Entropy Guided Transformation Learning: Applications.
  9. General ETL Modeling for NLP Tasks.
  10. Part
  11. of
  12. Speech Tagging.
  13. Phrase Chunking.
  14. Named Entity Recognition.
  15. Semantic Role Labeling.
  16. Conclusions.
  17. Appendices.

Please Login to submit errata.

No errata are currently published