Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/708
Title: Online Social Media Content Delivery
Other Titles: A Data-Driven Approach /
Authors: Wang, Zhi. ;;Zhu, Wenwu. ;;Yang, Shiqiang. ;
subject: Computer Science;Artificial Intelligence;Application Software;Computer Science;Information Systems Applications;Artificial Intelligence and Robotics;Computer Appl. in Social and Behavioral Sciences. ;
Year: 2018
place: Singapore :
Publisher: Springer Singapore :
Imprint: Springer,
Series/Report no.: SpringerBriefs in Computer Science, ; 2191-5768. ;
SpringerBriefs in Computer Science, ; 2191-5768. ;
Abstract: This book explains how to use a data-driven approach to design strategies for social media content delivery. It first introduces readers to how social information can be effectively gathered for big data analysis, which provides content delivery intelligence. Secondly, the book describes data-driven models to capture information diffusion in online social networks and social media content propagation and popularity, before presenting prediction models for social media content delivery. By addressing the resource allocation and content replication aspects of social media content delivery, the book presents the latest data-driven strategies. In closing, it outlines a number of potential research directions regarding social media content delivery. ;
Description: 

QA76.76.A65 ;
Printed edition: ; 9789811027734. ;
SpringerLink (Online service) ;
005.7 ; 23 ;

URI: http://localhost/handle/Hannan/708
ISBN: 9789811027741 ;
9789811027734 (print) ;
More Information: XI, 109 p. 64 illus. ; online resource. ;
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
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Title: Online Social Media Content Delivery
Other Titles: A Data-Driven Approach /
Authors: Wang, Zhi. ;;Zhu, Wenwu. ;;Yang, Shiqiang. ;
subject: Computer Science;Artificial Intelligence;Application Software;Computer Science;Information Systems Applications;Artificial Intelligence and Robotics;Computer Appl. in Social and Behavioral Sciences. ;
Year: 2018
place: Singapore :
Publisher: Springer Singapore :
Imprint: Springer,
Series/Report no.: SpringerBriefs in Computer Science, ; 2191-5768. ;
SpringerBriefs in Computer Science, ; 2191-5768. ;
Abstract: This book explains how to use a data-driven approach to design strategies for social media content delivery. It first introduces readers to how social information can be effectively gathered for big data analysis, which provides content delivery intelligence. Secondly, the book describes data-driven models to capture information diffusion in online social networks and social media content propagation and popularity, before presenting prediction models for social media content delivery. By addressing the resource allocation and content replication aspects of social media content delivery, the book presents the latest data-driven strategies. In closing, it outlines a number of potential research directions regarding social media content delivery. ;
Description: 

QA76.76.A65 ;
Printed edition: ; 9789811027734. ;
SpringerLink (Online service) ;
005.7 ; 23 ;

URI: http://localhost/handle/Hannan/708
ISBN: 9789811027741 ;
9789811027734 (print) ;
More Information: XI, 109 p. 64 illus. ; online resource. ;
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9789811027734.pdf4.73 MBAdobe PDFThumbnail
Preview File
Title: Online Social Media Content Delivery
Other Titles: A Data-Driven Approach /
Authors: Wang, Zhi. ;;Zhu, Wenwu. ;;Yang, Shiqiang. ;
subject: Computer Science;Artificial Intelligence;Application Software;Computer Science;Information Systems Applications;Artificial Intelligence and Robotics;Computer Appl. in Social and Behavioral Sciences. ;
Year: 2018
place: Singapore :
Publisher: Springer Singapore :
Imprint: Springer,
Series/Report no.: SpringerBriefs in Computer Science, ; 2191-5768. ;
SpringerBriefs in Computer Science, ; 2191-5768. ;
Abstract: This book explains how to use a data-driven approach to design strategies for social media content delivery. It first introduces readers to how social information can be effectively gathered for big data analysis, which provides content delivery intelligence. Secondly, the book describes data-driven models to capture information diffusion in online social networks and social media content propagation and popularity, before presenting prediction models for social media content delivery. By addressing the resource allocation and content replication aspects of social media content delivery, the book presents the latest data-driven strategies. In closing, it outlines a number of potential research directions regarding social media content delivery. ;
Description: 

QA76.76.A65 ;
Printed edition: ; 9789811027734. ;
SpringerLink (Online service) ;
005.7 ; 23 ;

URI: http://localhost/handle/Hannan/708
ISBN: 9789811027741 ;
9789811027734 (print) ;
More Information: XI, 109 p. 64 illus. ; online resource. ;
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9789811027734.pdf4.73 MBAdobe PDFThumbnail
Preview File