04474nam 22007815 450 991037390520332120251113200116.0981-15-1216-710.1007/978-981-15-1216-2(CKB)4100000010118971(DE-He213)978-981-15-1216-2(MiAaPQ)EBC6028045(PPN)242843271(EXLCZ)99410000001011897120200124d2020 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierDeep Learning-Based Approaches for Sentiment Analysis /edited by Basant Agarwal, Richi Nayak, Namita Mittal, Srikanta Patnaik1st ed. 2020.Singapore :Springer Nature Singapore :Imprint: Springer,2020.1 online resource (XII, 319 p.) Algorithms for Intelligent Systems,2524-7573981-15-1215-9 Includes bibliographical references.Chapter 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.This 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. .Algorithms for Intelligent Systems,2524-7573Signal processingData miningImage processingDigital techniquesComputer visionNatural language processing (Computer science)Computational intelligenceNeural networks (Computer science)Signal, Speech and Image ProcessingData Mining and Knowledge DiscoveryComputer Imaging, Vision, Pattern Recognition and GraphicsNatural Language Processing (NLP)Computational IntelligenceMathematical Models of Cognitive Processes and Neural NetworksSignal processing.Data mining.Image processingDigital techniques.Computer vision.Natural language processing (Computer science).Computational intelligence.Neural networks (Computer science).Signal, Speech and Image Processing.Data Mining and Knowledge Discovery.Computer Imaging, Vision, Pattern Recognition and Graphics.Natural Language Processing (NLP).Computational Intelligence.Mathematical Models of Cognitive Processes and Neural Networks.006.31Agarwal Basantedthttp://id.loc.gov/vocabulary/relators/edtNayak Richiedthttp://id.loc.gov/vocabulary/relators/edtMittal Namitaedthttp://id.loc.gov/vocabulary/relators/edtPatnaik Srikantaedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910373905203321Deep Learning-Based Approaches for Sentiment Analysis2517324UNINA