Entropy Guided Transformation Learning: Algorithms and Applications (SpringerBriefs in Computer Science) Paperback - 2012 - 2012th Edition
by Santos, Cícero Nogueira dos; Milidiú, Ruy Luiz
From the rear cover
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.
Details
- Title Entropy Guided Transformation Learning: Algorithms and Applications (SpringerBriefs in Computer Science)
- Author Santos, Cícero Nogueira dos; Milidiú, Ruy Luiz
- Binding Paperback
- Edition number 2012th
- Edition 2012
- Language ENG
- Publisher Springer
- Date 2012-03
- ISBN 9781447129776
-
Themes
- Aspects (Academic): Science/Technology Aspects
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Entropy Guided Transformation Learning: Algorithms and Applications (SpringerBriefs in Computer Science)
by dos Santos, CÃcero Nogueira; Milidiú, Ruy Luiz
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