Multimodal Analytics for Next-Generation Big Data Technologies and Applications - Hardcover

Hardcover

ISBN 10: 3319975978 ISBN 13: 9783319975979

Publisher: Springer, 2019

Synopsis

This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal data; unsupervised learning strategies for big multimodal data; supervised learning strategies for big multimodal data; and multimodal big data processing and applications.

The book will be of value to researchers, professionals and students in engineering and computer science, particularly those engaged with image and speech processing, multimodal information processing, data science, and artificial intelligence.

About this title

From the Back Cover

This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal data; unsupervised learning strategies for big multimodal data; supervised learning strategies for big multimodal data; and multimodal big data processing and applications.

The book will be of value to researchers, professionals and students in engineering and computer science, particularly those engaged with image and speech processing, multimodal information processing, data science, and artificial intelligence.

Edition details

• Publisher: Springer
• Publication date: 2019
• Language: English
• ISBN 10: 3319975978
• ISBN 13: 9783319975979
• Binding: Hardcover
• Edition number: 1
• Number of pages: 406
• Editor: Seng Kah Phooi, Ang Li-minn, Liew Alan Wee-Chung, Gao Junbin