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001			387387
003			ES-MaUEC
005			20230102122330.0
007			cr nn 008mamaa
008			220601s2021 sz | s |||| 0|eng d
020			_a9783031021800
024	7		_a10.1007/978-3-031-02180-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
050		4	_aQA76.9.N38 _b2021
100	1		_aSøgaard, Anders _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aExplainable Natural Language Processing _cby Anders Søgaard.
250			_a1st edition 2021
264		1	_aCham _bSpringer International Publishing _c2021
300			_a1 recurso en línea (XV, 107 páginas) _b
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Human Language Technologies _x1947-4059
505	0		_aAcknowledgments -- Introduction -- A Framework for Explainable NLP -- Local-Backward Explanations -- Global-Backward Explanations -- Local-Forward Explanations of Intermediate Representations -- Global-Forward Explanations of Intermediate Representations -- Local-Forward Explanations of Continuous Output -- Global-Forward Explanations of Continuous Output -- Local-Forward Explanations of Discrete Output -- Global-Forward Explanations of Discrete Output -- Evaluating Explanations -- Perspectives -- Resources -- Bibliography -- Author's Biography .
520			_aThis book presents a taxonomy framework and survey of methods relevant to explaining the decisions and analyzing the inner workings of Natural Language Processing (NLP) models. The book is intended to provide a snapshot of Explainable NLP, though the field continues to rapidly grow. The book is intended to be both readable by first-year M.Sc. students and interesting to an expert audience. The book opens by motivating a focus on providing a consistent taxonomy, pointing out inconsistencies and redundancies in previous taxonomies. It goes on to present (i) a taxonomy or framework for thinking about how approaches to explainable NLP relate to one another; (ii) brief surveys of each of the classes in the taxonomy, with a focus on methods that are relevant for NLP; and (iii) a discussion of the inherent limitations of some classes of methods, as well as how to best evaluate them. Finally, the book closes by providing a list of resources for further research on explainability.
776	0	8	_iPrinted edition: _z9783031001918
776	0	8	_iPrinted edition: _z9783031010521
776	0	8	_iPrinted edition: _z9783031033087
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02180-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSynthesis Collection of Technology_2021
999			_c387387 _d387387