About this book
Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer.
This volume covers the three main topics of: textual preprocessing and sentiment analysis methods; frameworks to process audio and visual data; and methods of textual, audio and visual features fusion.
The inclusion of key visualization and case studies will enable readers to understand better these approaches.
Aimed at the Natural Language Processing, Affective Computing and Artificial Intelligence audiences, this comprehensive volume will appeal to a wide readership and will help readers to understand key details on multimodal sentiment analysis.
- Book Title Multimodal Sentiment Analysis
- Series Title Socio-Affective Computing
- Series Abbreviated Title Socio-Affect. Comput.
- DOI https://doi.org/10.1007/978-3-319-95020-4
- Copyright Information Springer International Publishing AG, part of Springer Nature 2018
- Publisher Name Springer, Cham
- eBook Packages Biomedical and Life Sciences Biomedical and Life Sciences (R0)
- Hardcover ISBN 978-3-319-95018-1
- Softcover ISBN 978-3-030-06956-8
- eBook ISBN 978-3-319-95020-4
- Series ISSN 2509-5706
- Series E-ISSN 2509-5714
- Edition Number 1
- Number of Pages XI, 214
- Number of Illustrations 9 b/w illustrations, 25 illustrations in colour
Multimedia Information Systems
Image Processing and Computer Vision
Natural Language Processing (NLP)
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