Big Data
8th CCF Conference, BigData 2020, Chongqing, China, October 22-24, 2020, Revised Selected Papers
Published on 1. April 2021
Book
Paperback/Softback
XVIII, 243 pages
978-981-16-0704-2 (ISBN)
Description
This book constitutes the proceedings of the 8th CCF Conference on Big Data, BigData 2020, held in Chongqing, China, in October 2020.
The 16 full papers presented in this volume were carefully reviewed and selected from 65 submissions. They present recent research on theoretical and technical aspects on big data, as well as on digital economy demands in big data applications.
More details
Series
Edition
1st ed. 2021
Language
English
Place of publication
Singapore
Singapore
Target group
Professional and scholarly
Illustrations
13 s/w Abbildungen, 85 farbige Abbildungen
XVIII, 243 p. 98 illus., 85 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 15 mm
Weight
406 gr
ISBN-13
978-981-16-0704-2 (9789811607042)
DOI
10.1007/978-981-16-0705-9
Schweitzer Classification
Other editions
Additional editions
Hong Mei | Weiguo Zhang | Wenfei Fan
Big Data
8th CCF Conference, BigData 2020, Chongqing, China, October 22-24, 2020, Revised Selected Papers
E-Book
03/2021
Springer
€53.49
Available for download
Content
A Short Text Classification Model Based on Cross-Layer Connected Gated Recurrent Unit Capsule Network.- Image Compressed Sensing using Neural Architecture Search.- Discovery of Sparse Formula Based on Elastic Network Method and its Application in Identification of Turbulent Boundary Layer Wall Function.- Rotation-Dpeak: Improving Density Peaks Selection for Imbalanced Data.- Introducing MDPSD, a Multimodal Dataset for Psychological Stress Detection.- Small-Scale Data Classification Based Deep Forest.- An Answer Sorting Method Combining Multiple Neural Networks and Attentional Mechanisms.- Optimal Subspace Analysis based on Information-Entropy Increment.- Link Prediction of Attention Flow Network Based on Maximum Entropy Model.- Graph Representation Learning using Attention Network.- Food Pairing Based on Generative Adversarial Networks.- Comparisons of Deep Neural Networks in Multi-Label Classification for Chinese Recipes.- Improving Word Alignment With Contextualized Embedding and Bilingual Dictionary.- Hypernetwork Model Based on Logistic Regression.- Multi Dimensional Evaluation of Middle School Students' Physical and Mental Quality and Intelligent Recommendation of Exercise Programs Based on Big Data Analysis.- Diversity-Aware Top-N Recommendation: A Deep Reinforcement Learning way.