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008			160804s2016 gw a s 001 0 eng d
020			_a9783662479094
024	7		_a10.1007/978-3-662-47909-4 _2doi
040			_aES-MaUEC
050		4	_aQA76.9.N38 _b.A53 2016 EB
082	0	4	_a006.35
245	0	0	_aAnaphora Resolution : _bAlgorithms, Resources, and Applications _cedited by Massimo Poesio, Roland Stuckardt, Yannick Versley
264		1	_aBerlin, Heidelberg _bSpringer Berlin Heidelberg _c2016
300			_a1 recurso en línea (X, 508 p.) _b30 ilustraciones, 4 ilustraciones en color
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	1		_aTheory and Applications of Natural Language Processing _x2192-032X
505	0		_aPreface -- 1.Introduction -- Part I Background -- 2.Linguistic and Cognitive Evidence About Anaphora -- 3. Early Approaches to Anaphora Resolution: Theoretically Inspired and Heuristic-Based -- Part II Resources -- 4.Annotated Corpora and Annotation Tools -- 5.Evaluation Metrics -- 6.Evaluation Campaigns -- 7.Preprocessing Technology -- 8.Off-the-shelf Tools -- Part III Algorithms -- 9.The Mention-Pair Model -- 10.Advanced Machine Learning Models for Coreference Resolution -- 11.Integer Linear Programming for Coreference Resolution -- 12.Extracting Anaphoric Agreement Properties from Corpora -- 13.Detecting Non-reference and Non-anaphoricity -- 14.Using Lexical and Encyclopedic Knowledge -- Part IV Applications -- 15.Coreference Applications to Summarization -- 16.Towards a Procedure Model for Developing Anaphora Processing Applications -- Part V Outlook -- 17.Challenges and Directions of Further Research -- Index.
520			_aThis book lays out a path leading from the linguistic and cognitive basics, to classical rule-based and machine learning algorithms, to todays state-of-the-art approaches, which use advanced empirically grounded techniques, automatic knowledge acquisition, and refined linguistic modeling to make a real difference in real-world applications. Anaphora and coreference resolution both refer to the process of linking textual phrases (and, consequently, the information attached to them) within as well as across sentence boundaries, and to the same discourse referent. The book offers an overview of recent research advances, focusing on practical, operational approaches and their applications. In part I (Background), it provides a general introduction, which succinctly summarizes the linguistic, cognitive, and computational foundations of anaphora processing and the key classical rule- and machine-learning-based anaphora resolution algorithms. Acknowledging the central importance of shared resources, part II (Resources) covers annotated corpora, formal evaluation, preprocessing technology, and off-the-shelf anaphora resolution systems. Part III (Algorithms) provides a thorough description of state-of-the-art anaphora resolution algorithms, covering enhanced machine learning methods as well as techniques for accomplishing important subtasks such as mention detection and acquisition of relevant knowledge. Part IV (Applications) deals with a selection of important anaphora and coreference resolution applications, discussing particular scenarios in diverse domains and distilling a best-practice model for systematically approaching new application cases. In the concluding part V (Outlook), based on a survey conducted among the contributing authors, the prospects of the research field of anaphora processing are discussed, and promising new areas of interdisciplinary cooperation and emerging application scenarios are identified. Given the books design, it can be used both as an accompanying text for advanced lectures in computational linguistics, natural language engineering, and computer science, and as a reference work for research and independent study. It addresses an audience that includes academic researchers, university lecturers, postgraduate students, advanced undergraduate students, industrial researchers, and software engineers.
710	2		_aSpringerLink (Online service) _0Local _9106996
942			_2lcc _cLE
988			_aEBOOK, EBSPRINGER
650		7	_aProceso en lenguaje natural (Informática) _0comprobar BNE20012033390 _2embne _9158738
700	1		_aPoesio, Massimo _eeditor literario _9100190 _0Local
700	1		_aStuckardt, Roland _eeditor literario _9100191 _0Local
700	1		_aVersley, Yannick _eeditor literario _9100192 _0Local
830		0	_aTheory and Applications of Natural Language Processing _x2192-032X _9134143
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-662-47909-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783662479094
907			_a.b12957434 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b16-09-17 _cm _dz _ei _feng _ggw _h0
945			_aQA79.9 .N38 .A53 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11599224 _z06-04-17
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