Multimodal Analytics for Next-Generation Big Data Technologies and Applications (Hardcover, 1st ed. 2019)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	July 2019
First published:	2019
Editors:	Kah Phooi Seng • Li-Minn Ang • Alan Wee-Chung Liew • Junbin Gao
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	391
Edition:	1st ed. 2019
ISBN-13:	978-3-319-97597-9
Categories:	Books > Computing & IT > Applications of computing > Databases > General
LSN:	3-319-97597-8
Barcode:	9783319975979

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