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Deep Learning-Based Approaches for Sentiment Analysis

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...

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Bibliographic Details
Other Authors: Agarwal, Basant (Editor), Nayak, Richi (Editor), Mittal, Namita (Editor), Patnaik, Srikanta (Editor)
Format: eBook
Language:English
Published: Singapore Springer Nature Singapore 2020, 2020
Edition:1st ed. 2020
Series:Algorithms for Intelligent Systems
Subjects:
Image Processing / Digital Techniques
Computer Vision
Computational Intelligence
Mathematical Models Of Cognitive Processes And Neural Networks
Data Mining
Computer Imaging, Vision, Pattern Recognition And Graphics
Neural Networks (computer Science) 
Signal, Speech And Image Processing
Data Mining And Knowledge Discovery
Natural Language Processing (nlp)
Signal Processing
Natural Language Processing (computer Science)
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Description
Summary: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.
Physical Description:XII, 319 p online resource
ISBN:9789811512162

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