Transactions on Large-Scale Data- and Knowledge-Centered Systems XLVII〈1st ed. 2021〉 : Special Issue on Digital Ecosystems and Social Networks

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Transactions on Large-Scale Data- and Knowledge-Centered Systems XLVII〈1st ed. 2021〉 : Special Issue on Digital Ecosystems and Social Networks

  • 著者名:Hameurlain, Abdelkader (EDT)/Tjoa, A Min (EDT)/Chbeir, Richard (EDT)
  • 価格 ¥10,117 (本体¥9,198)
  • Springer(2021/01/16発売)
  • 春うらら!Kinoppy 電子書籍・電子洋書 全点ポイント30倍キャンペーン(~3/15)
  • ポイント 2,730pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9783662629185
  • eISBN:9783662629192

ファイル: /

Description

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability.

This, the 47th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, constitutes a special issue focusing on Digital Ecosystems and Social Networks. The 9 revised selected papers cover topics that include Social Big Data, Data Analysis, Cloud-Based Feedback, Experience Ecosystems, Pervasive Environments, and Smart Systems.

Table of Contents

Mapping Experience Ecosystems as Emergent Actor-Created Spaces.- A Semantic-Based Strategy to Model Multimedia Social Networks.- Social Big Data: Concepts and Theory.- Social Big Data: Case Studies.- Data Analysis in Social Networks: A Case Study.- Smart Services Using Voice and Images.- Big Spatial and Spatio-Temporal Data Analytics Systems.- Cloud-Based e-Feedback Services Using Performance Analysis: A Linear Approach.- Semantic-Based Automatic Generation of Reconfigurable Distributed Mobile Applications in Pervasive Environments.

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