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007			cr nn 008mamaa
008			220601s2016 sz | s |||| 0|eng d
020			_a9783031021640
024	7		_a10.1007/978-3-031-02164-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aP308 _b2016 EB
100	1		_aWilliams, Philip _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686338 _q(Philip James)
245	1	0	_aSyntax-based Statistical Machine Translation _cby Philip Williams, Rico Sennrich, Matt Post, Philipp Koehn
250			_a1st edition 2016
264		1	_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XVIII, 190 páginas)
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		_aPreface -- Acknowledgments -- Models -- Learning from Parallel Text -- Decoding I: Preliminaries -- Decoding II: Tree Decoding -- Decoding III: String Decoding -- Selected Topics -- Closing Remarks -- Bibliography -- Authors' Biographies -- Author Index -- Index.
520			_aThis unique book provides a comprehensive introduction to the most popular syntax-based statistical machine translation models, filling a gap in the current literature for researchers and developers in human language technologies. While phrase-based models have previously dominated the field, syntax-based approaches have proved a popular alternative, as they elegantly solve many of the shortcomings of phrase-based models. The heart of this book is a detailed introduction to decoding for syntax-based models. The book begins with an overview of synchronous-context free grammar (SCFG) and synchronous tree-substitution grammar (STSG) along with their associated statistical models. It also describes how three popular instantiations (Hiero, SAMT, and GHKM) are learned from parallel corpora. It introduces and details hypergraphs and associated general algorithms, as well as algorithms for decoding with both tree and string input. Special attention is given to efficiency, including search approximations such as beam search and cube pruning, data structures, and parsing algorithms. The book consistently highlights the strengths (and limitations) of syntax-based approaches, including their ability to generalize phrase-based translation units, their modeling of specific linguistic phenomena, and their function of structuring the search space.
988			_aSynthesis Collection of Technology_2016
650		7	_2embne _9140340 _aTraducción automática
650		7	_2embne _9140337 _aTraducción _xProceso de datos
700	1		_aSennrich, Rico _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686339
700	1		_aPost, Matt _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686340
700	1		_aKoehn, Philipp _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686341
776	0	8	_iPrinted edition: _z9783031010361
776	0	8	_iPrinted edition: _z9783031032929
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02164-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2023 _dz _esc _zSI