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008			180523s2018 si |||| o |||| 0|eng
010			_a 2019745366
020			_a9789811052088 (Hbk)
024	7		_a10.1007/978-981-10-5209-5 _2doi
035			_a(DE-He213)978-981-10-5209-5
040			_aDLC _beng _epn _erda _cIISERB
072		7	_aCOM004000 _2bisacsh
072		7	_aUYQ _2bicssc
072		7	_aUYQ _2thema
082	0	4	_a006.3 D41D _223
245	0	0	_aDeep Learning in Natural Language Processing _cedited by Li Deng, Yang Liu.
250			_a1st ed. 2018.
260			_aSingapore: _bSpringer-Nature, _c2018.
300			_aXVII, 329 pages
505	0		_aChapter 1: A Joint Introduction to Natural Language Processing and to Deep Learning -- Chapter 2: Deep Learning in Conversational Language Understanding -- Chapter 3: Deep Learning in Spoken and Text-Based Dialogue Systems -- Chapter 4: Deep Learning in Lexical Analysis and Parsing -- Chapter 5: Deep Learning in Knowledge Graph -- Chapter 6: Deep Learning in Machine Translation -- Chapter 7: Deep Learning in Question Answering -- Chapter 8: Deep Learning in Sentiment Analysis -- Chapter 9: Deep Learning in Social Computing -- Chapter 10: Deep Learning in Natural Language Generation from Images -- 11. Epilogue: Frontiers of NLP in the Deep Learning Era.
520			_aIn recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.
650		0	_aArtificial intelligence. _930465
650		0	_aMathematical statistics. _930466
650		0	_aNatural language processing (Computer science). _930467
650	1	4	_aArtificial Intelligence. _930468
650	2	4	_aNatural Language Processing (NLP). _930469
650	2	4	_aNatural Language Processing (NLP). _930469
650	2	4	_aProbability and Statistics in Computer Science. _930470
700	1		_aDeng, Li, _eeditor. _930471
700	1		_aLiu, Yang. _eeditor. _930472
776	0	8	_iPrint version: _tDeep learning in natural language processing. _z9789811052088 _w(DLC) 2018934459
776	0	8	_iPrinted edition: _z9789811052088
776	0	8	_iPrinted edition: _z9789811052101
776	0	8	_iPrinted edition: _z9789811338489
906			_a0 _bibc _corigres _du _encip _f20 _gy-gencatlg
942			_2ddc _cBK
999			_c10360 _d10360