Big Data : 9th CCF Conference, BigData 2021, Guangzhou, China, January 8–10, 2022, Revised Selected Papers / / edited by Xiangke Liao, Wei Zhao, Enhong Chen, Nong Xiao, Li Wang, Yang Gao, Yinghuan Shi, Changdong Wang, Dan Huang

• Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2022
• Edizione: 1st ed. 2022.
• Descrizione fisica: 1 online resource (334 pages)
• Disciplina: 006.3
• Soggetto topico: Artificial intelligence; Computer engineering; Computer networks; Education - Data processing; Image processing - Digital techniques; Computer vision; Data structures (Computer science); Information theory; Artificial Intelligence; Computer Engineering and Networks; Computers and Education; Computer Imaging, Vision, Pattern Recognition and Graphics; Data Structures and Information Theory
• Persona (resp. second.): LiaoXiangke
• Nota di contenuto: Big Data Analysis and Applications -- Big Data and Deep Learning -- Big Data Intelligent Algorithms -- Big Data Privacy and Security -- Image and Natural Language Big Data.
• Sommario/riassunto: This book constitutes the proceedings of the 9th CCF Conference on Big Data, BigData 2021, held in Guangzhou, China, in January 2022. Due to the COVID-19 pandemic BigData 2021 was postponed to 2022. The 21 full papers presented in this volume were carefully reviewed and selected from 66 submissions. They present recent research on theoretical and technical aspects on big data, as well as on digital economy demands in big data applications. .
• Titolo autorizzato: Big Data
• ISBN: 981-16-9708-6; 981-16-9709-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910743387103321
• Lo trovi qui: Univ. Federico II
• Serie: Communications in Computer and Information Science, . 1865-0937 ; ; 1496