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007			cr nn 008mamaa
008			220601s2016 sz | s |||| 0|eng d
020			_a9783031021633
024	7		_a10.1007/978-3-031-02163-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.N38 _b2016 EB
100	1		_aStrötgen, Jannik _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687405
245	1	0	_aDomain-Sensitive Temporal Tagging _cby Jannik Strötgen, Michael Gertz
250			_a1st edition 2016
264		1	_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XVII, 133 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		_aList of Figures -- List of Tables -- Preface -- Acknowledgments -- Introduction -- The Concept of Time -- Foundations of Temporal Tagging -- Domain-sensitive Temporal Tagging -- Techniques and Tools -- Summary and Future Research Directions -- Bibliography -- Authors' Biographies -- Index.
520			_aThis book covers the topic of temporal tagging, the detection of temporal expressions and the normalization of their semantics to some standard format. It places a special focus on the challenges and opportunities of domain-sensitive temporal tagging. After providing background knowledge on the concept of time, the book continues with a comprehensive survey of current research on temporal tagging. The authors provide an overview of existing techniques and tools, and highlight key issues that need to be addressed. This book is a valuable resource for researchers and application developers who need to become familiar with the topic and want to know the recent trends, current tools and techniques, as well as different application domains in which temporal information is of utmost importance. Due to the prevalence of temporal expressions in diverse types of documents and the importance of temporal information in any information space, temporal tagging is an important task in natural language processing (NLP), and applications of several domains can benefit from the output of temporal taggers to provide more meaningful and useful results. In recent years, temporal tagging has been an active field in NLP and computational linguistics. Several approaches to temporal tagging have been proposed, annotation standards have been developed, gold standard data sets have been created, and research competitions have been organized. Furthermore, some temporal taggers have also been made publicly available so that temporal tagging output is not just exploited in research, but is finding its way into real world applications. In addition, this book particularly focuses on domain-specific temporal tagging of documents. This is a crucial aspect as different types of documents (e.g., news articles, narratives, and colloquial texts) result in diverse challenges for temporal taggers and should be processed in a domain-sensitive manner.
988			_aSynthesis Collection of Technology_2016
650		7	_2embne _9666075 _aLingüística computacional
650		7	_2embne _9158738 _aProceso en lenguaje natural (Informática)
650		7	_2embne _9678605 _aLenguajes de programación
700	1		_aGertz, Michael _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687406
776	0	8	_iPrinted edition: _z9783031010354
776	0	8	_iPrinted edition: _z9783031032912
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02163-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI