Big Data: 10th CCF Conference, BigData 2022, Chengdu, China, November 18-20, 2022, Proceedings
This book constitutes the refereed proceedings of the 10th CCF Conference on BigData 2022, which took place in Chengdu, China, in November 2022. 

The 8 full papers presented in this volume were carefully reviewed and selected from 28 submissions. The topics of accepted papers include theories and methods of data science, algorithms and applications of big data.
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Big Data: 10th CCF Conference, BigData 2022, Chengdu, China, November 18-20, 2022, Proceedings
This book constitutes the refereed proceedings of the 10th CCF Conference on BigData 2022, which took place in Chengdu, China, in November 2022. 

The 8 full papers presented in this volume were carefully reviewed and selected from 28 submissions. The topics of accepted papers include theories and methods of data science, algorithms and applications of big data.
69.99 In Stock
Big Data: 10th CCF Conference, BigData 2022, Chengdu, China, November 18-20, 2022, Proceedings

Big Data: 10th CCF Conference, BigData 2022, Chengdu, China, November 18-20, 2022, Proceedings

Big Data: 10th CCF Conference, BigData 2022, Chengdu, China, November 18-20, 2022, Proceedings

Big Data: 10th CCF Conference, BigData 2022, Chengdu, China, November 18-20, 2022, Proceedings

eBook1st ed. 2022 (1st ed. 2022)

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Overview

This book constitutes the refereed proceedings of the 10th CCF Conference on BigData 2022, which took place in Chengdu, China, in November 2022. 

The 8 full papers presented in this volume were carefully reviewed and selected from 28 submissions. The topics of accepted papers include theories and methods of data science, algorithms and applications of big data.

Product Details

ISBN-13: 9789811983313
Publisher: Springer-Verlag New York, LLC
Publication date: 11/23/2022
Series: Communications in Computer and Information Science , #1709
Sold by: Barnes & Noble
Format: eBook
File size: 28 MB
Note: This product may take a few minutes to download.

Table of Contents

Searching Similar Trajectories Based on Shape.- Unsupervised Discovery of Disentangled Interpretable Directions for Layer-wise GAN.- ASNN: Accelerated Searching for Natural Neighbors.- ASNN: Accelerated Searching for Natural Neighbors.- ASNN: Accelerated Searching for Natural Neighbors.- A Data-to-Text Generation Model with Deduplicated Content Planning Searching Similar Trajectories Based on Shape.- Clustering-Enhanced Knowledge Graph Embedding.- FCI:Feature Cross and User Interest Network.
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