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001			978-1-4471-2978-3
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008			120314s2012 xxk| s |||| 0|eng d
020			_a9781447129783 _9978-1-4471-2978-3
024	7		_a10.1007/978-1-4471-2978-3 _2doi
050		4	_aQ337.5
050		4	_aTK7882.P3
072		7	_aUYQP _2bicssc
072		7	_aCOM016000 _2bisacsh
082	0	4	_a006.4 _223
100	1		_aSantos, Cícero Nogueira. _eauthor.
245	1	0	_aEntropy Guided Transformation Learning: Algorithms and Applications _h[electronic resource] / _cby Cícero Nogueira Santos, Ruy Luiz Milidiú.
264		1	_aLondon : _bSpringer London, _c2012.
300			_aXIII, 78p. 10 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringerBriefs in Computer Science, _x2191-5768
505	0		_aPreface -- 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.
520			_aEntropy 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.
650		0	_aComputer science.
650		0	_aTranslators (Computer programs).
650		0	_aOptical pattern recognition.
650		0	_aComputational linguistics.
650	1	4	_aComputer Science.
650	2	4	_aPattern Recognition.
650	2	4	_aLanguage Translation and Linguistics.
650	2	4	_aComputational Linguistics.
700	1		_aMilidiú, Ruy Luiz. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781447129776
830		0	_aSpringerBriefs in Computer Science, _x2191-5768
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4471-2978-3
912			_aZDB-2-SCS
999			_c16121 _d16121