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Multimodal analytics for next-genera...

Seng, Kah Phooi.

Multimodal analytics for next-generation big data technologies and applications

Record Type:	Electronic resources : Monograph/item
Title/Author:	Multimodal analytics for next-generation big data technologies and applicationsedited by Kah Phooi Seng ... [et al.].
other author:	Seng, Kah Phooi.
Published:	Cham :Springer International Publishing :2019.
Description:	xv, 391 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Big data.
Online resource:	https://doi.org/10.1007/978-3-319-97598-6
ISBN:	9783319975986$q(electronic bk.)

Multimodal analytics for next-generation big data technologies and applications
Multimodal analytics for next-generation big data technologies and applications[electronic resource] /edited by Kah Phooi Seng ... [et al.]. - Cham :Springer International Publishing :2019. - xv, 391 p. :ill., digital ;24 cm.

Foundations and Principles -- Advanced Information and Knowledge Processing -- Advanced Models and Architectures -- Advanced Applications and Future Trends.

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.

ISBN: 9783319975986$q(electronic bk.)

Standard No.: 10.1007/978-3-319-97598-6doiSubjects--Topical Terms:

609582
Big data.

LC Class. No.: QA76.9.B45 / M85 2019

Dewey Class. No.: 005.7

Multimodal analytics for next-generation big data technologies and applications
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505 0 $a Foundations and Principles -- Advanced Information and Knowledge Processing -- Advanced Models and Architectures -- Advanced Applications and Future Trends.
520 $a 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.
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