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020			_a9789811512162
024	7		_a10.1007/978-981-15-1216-2 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9 .N38 _b2020 EB
245	0	0	_aDeep Learning-Based Approaches for Sentiment Analysis _cedited by Basant Agarwal, Richi Nayak, Namita Mittal, Srikanta Patnaik
250			_aPrimera edición 2020
264		1	_aSingapore _bSpringer _c2020
300			_a1 recurso en línea (XII, 319 páginas)
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aAlgorithms for Intelligent Systems _x2524-7565
490	0		_aEngineering (Springer-11647)
505	0		_aChapter 1. Application of Deep Learning Approaches for Sentiment Analysis: A Survey -- Chapter 2. Recent Trends and Advances in Deep Learning based Sentiment Analysis -- Chapter 3. - Deep Learning Adaptation with Word Embeddings for Sentiment Analysis on Online Course Reviews -- Chapter 4. Toxic Comment Detection in Online Discussions -- Chapter 5. Aspect Based Sentiment Analysis of Financial Headlines and Microblogs -- Chapter 6. Deep Learning based frameworks for Aspect Based Sentiment Analysis -- Chapter 7. Transfer Learning for Detecting Hateful Sentiments in Code Switched Language -- Chapter 8. Multilingual Sentiment Analysis -- Chapter 9. Sarcasm Detection using deep learning -- Chapter 10. Deep Learning Approaches for Speech Emotion Recognition -- Chapter 11. Bidirectional Long Short Term Memory Based Spatio-Temporal In Community Question Answering -- Chapter 12. Comparing Deep Neural Networks to Traditional Models for Sentiment Analysis in Turkish Language.
520	3		_aThis book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge solutions for the most common and difficult challenges faced in sentiment analysis research. Providing detailed explanations of the methodologies, the book is a valuable resource for researchers as well as newcomers to the field. .
988			_aPrimersemestre_2020_Engineering
650		7	_2embne _aProceso en lenguaje natural (Informática) _9158738
700	1		_aAgarwal, Basant _eeditor _997805
700	1		_aNayak, Richi _eeditor
700	1		_aMittal, Namita _eeditor _997806
700	1		_aPatnaik, Srikanta _eeditor
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9789811512155
776	0	8	_iPrinted edition: _z9789811512179
776	0	8	_iPrinted edition: _z9789811512186
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-15-1216-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b04/2020 _dz _eu _zSI