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008			220601s2014 sz | s |||| 0|eng d
020			_a9783031021534
024	7		_a10.1007/978-3-031-02153-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050			_aPE1128.3 _b2014 EB
100	1		_aLeacock, Claudia _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686955
245	1	0	_aAutomated Grammatical Error Detection for Language Learners _cby Claudia Leacock, Michael Gamon, Joel Alejandro Mejia, Martin Chodorow
250			_a1st edition 2014
264		1	_aCham _bSpringer International Publishing _c2014
300			_a1 recurso en línea (XV, 154 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		_aAcknowledgments -- Introduction -- Background -- Special Problems of Language Learners -- Evaluating Error Detection Systems -- Data-Driven Approaches to Articles and Prepositions -- Collocation Errors -- Different Errors and Different Approaches -- Annotating Learner Errors -- Emerging Directions -- Conclusion -- Bibliography -- Authors' Biographies .
520			_aIt has been estimated that over a billion people are using or learning English as a second or foreign language, and the numbers are growing not only for English but for other languages as well. These language learners provide a burgeoning market for tools that help identify and correct learners' writing errors. Unfortunately, the errors targeted by typical commercial proofreading tools do not include those aspects of a second language that are hardest to learn. This volume describes the types of constructions English language learners find most difficult: constructions containing prepositions, articles, and collocations. It provides an overview of the automated approaches that have been developed to identify and correct these and other classes of learner errors in a number of languages. Error annotation and system evaluation are particularly important topics in grammatical error detection because there are no commonly accepted standards. Chapters in the book describe the options available to researchers, recommend best practices for reporting results, and present annotation and evaluation schemes. The final chapters explore recent innovative work that opens new directions for research. It is the authors' hope that this volume will continue to contribute to the growing interest in grammatical error detection by encouraging researchers to take a closer look at the field and its many challenging problems.
988			_aSynthesis Collection of Technology_2014
650		7	_2embne _9449405 _aLengua inglesa _xEstudio y enseñanza
650		7	_2embne _9141397 _aLengua inglesa _xEnseñanza asistida por ordenador
650		7	_2embne _9666075 _aLingüística computacional
700	1		_aGamon, Michael _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686957
700	1		_aMejia, Joel Alejandro, _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687394 _d1985-
700	1		_aChodorow, Martin _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686956
776	0	8	_iPrinted edition: _z9783031010255
776	0	8	_iPrinted edition: _z9783031032813
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02153-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI