Multimodal Analytics for Next-Generation Big Data Technologies and Applications

✍ Scribed by Kah Phooi Seng, Li-minn Ang, Alan Wee-Chung Liew, Junbin Gao

• Publisher: Springer International Publishing
• Year: 2019
• Tongue: English
• Leaves: 391
• Edition: 1st ed.
• Category: Library

✦ 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.

✦ Table of Contents

Front Matter ....Pages i-xv
Front Matter ....Pages 1-1
Multimodal Information Processing and Big Data Analytics in a Digital World (Kah Phooi Seng, Li-minn Ang, Alan Wee-Chung Liew, Junbin Gao)....Pages 3-9
Front Matter ....Pages 11-11
Speaker-Independent Multimodal Sentiment Analysis for Big Data (Erik Cambria, Soujanya Poria, Amir Hussain)....Pages 13-43
Multimodal Big Data Affective Analytics (Nusrat Jahan Shoumy, Li-minn Ang, D. M. Motiur Rahaman)....Pages 45-71
Hybrid Feature-Based Sentiment Strength Detection for Big Data Applications (Yanghui Rao, Haoran Xie, Fu Lee Wang, Leonard K. M. Poon, Endong Zhu)....Pages 73-91
Front Matter ....Pages 93-93
Multimodal Co-clustering Analysis of Big Data Based on Matrix and Tensor Decomposition (Hongya Zhao, Zhenghong Wei, Hong Yan)....Pages 95-124
Bi-clustering by Multi-objective Evolutionary Algorithm for Multimodal Analytics and Big Data (Maryam Golchin, Alan Wee-Chung Liew)....Pages 125-150
Unsupervised Learning on Grassmann Manifolds for Big Data (Boyue Wang, Junbin Gao)....Pages 151-180
Front Matter ....Pages 181-181
Multi-product Newsvendor Model in Multi-task Deep Neural Network with Norm Regularization for Big Data (Yanfei Zhang)....Pages 183-205
Recurrent Neural Networks for Multimodal Time Series Big Data Analytics (Mingyuan Bai, Boyan Zhang)....Pages 207-243
Scalable Multimodal Factorization for Learning from Big Data (Quan Do, Wei Liu)....Pages 245-268
Front Matter ....Pages 269-269
Big Multimodal Visual Data Registration for Digital Media Production (Hansung Kim, Adrian Hilton)....Pages 271-297
A Hybrid Fuzzy Football Scenes Classification System for Big Video Data (Song Wei, Hani Hagras)....Pages 299-318
Multimodal Big Data Fusion for Traffic Congestion Prediction (Taiwo Adetiloye, Anjali Awasthi)....Pages 319-335
Parallel and Distributed Computing for Processing Big Image and Video Data (Praveen Kumar, Apeksha Bodade, Harshada Kumbhare, Ruchita Ashtankar, Swapnil Arsh, Vatsal Gosar)....Pages 337-360
Multimodal Approaches in Analysing and Interpreting Big Social Media Data (Eugene Ch’ng, Mengdi Li, Ziyang Chen, Jingbo Lang, Simon See)....Pages 361-391

✦ Subjects

Computer Science