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[null,"1.","Record Nr.",null,"UNINA9910373905203321"]
[null,null,"Titolo",null,"Deep Learning-Based Approaches for Sentiment Analysis / / edited by Basant Agarwal, Richi Nayak, Namita Mittal, Srikanta Patnaik"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2020"]
[null,null,"ISBN",null,"981-15-1216-7"]
[null,null,"Edizione",null,"[1st ed. 2020.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XII, 319 p.)"]
[null,null,"Collana",null,"Algorithms for Intelligent Systems, , 2524-7573"]
[null,null,"Disciplina",null,"006.31"]
[null,null,"Soggetti",null,"Signal processing"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Image processing - Digital techniques"]
[{"$nulls":4},"Computer vision"]
[{"$nulls":4},"Natural language processing (Computer science)"]
[{"$nulls":4},"Computational intelligence"]
[{"$nulls":4},"Neural networks (Computer science)"]
[{"$nulls":4},"Signal, Speech and Image Processing"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Computer Imaging, Vision, Pattern Recognition and Graphics"]
[{"$nulls":4},"Natural Language Processing (NLP)"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Mathematical Models of Cognitive Processes and Neural Networks"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"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 "]
[{"$nulls":4},"Community Question Answering -- Chapter 12. Comparing Deep Neural Networks to Traditional Models for Sentiment Analysis in Turkish Language."]
[null,null,null,"Sommario/riassunto","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. ."]