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Deep Learning-Based Approaches for Sentiment Analysis

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Deep Learning-Based Approaches for Sentiment Analysis/ edited by Basant Agarwal, Richi Nayak, Namita Mittal, Srikanta Patnaik.
other author:	Agarwal, Basant.
Description:	XII, 319 p.online resource. :
Contained By:	Springer Nature eBook
Subject:	Signal processing. -
Online resource:	https://doi.org/10.1007/978-981-15-1216-2
ISBN:	9789811512162

Deep Learning-Based Approaches for Sentiment Analysis
Deep Learning-Based Approaches for Sentiment Analysis[electronic resource] /edited by Basant Agarwal, Richi Nayak, Namita Mittal, Srikanta Patnaik. - 1st ed. 2020. - XII, 319 p.online resource. - Algorithms for Intelligent Systems,2524-7565. - Algorithms for Intelligent Systems,.

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. .

ISBN: 9789811512162

Standard No.: 10.1007/978-981-15-1216-2doiSubjects--Topical Terms:

561459
Signal processing.

LC Class. No.: TK5102.9

Dewey Class. No.: 621.382

Deep Learning-Based Approaches for Sentiment Analysis
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