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Transactions on Large-Scale Data- and Knowledge-Centered Systems XLV

- Special Issue on Data Management and Knowledge Extraction in Digital Ecosystems

Bag om Transactions on Large-Scale Data- and Knowledge-Centered Systems XLV

Interoperable Data Extraction and Analytics Queries over Blockchains.- Exploiting Twitter for Informativeness Classification in Disaster Situations.- COTILES: Leveraging Content and Structure for Evolutionary Community Detection.- A Weighted Feature-Based Image Quality Assessment Framework in Real-Time.- Sharing Knowledge in Digital Ecosystems Using Semantic Multimedia Big Data.- Facilitating and Managing Machine Learning and Data Analysis Tasks in Big Data Environments Using Web and Microservice Technologies.- Stable Marriage Matching for Homogenizing Load Distribution in a Cloud Data Center.- A Sentiment Analysis Software Framework for the Support of Business Information Architecture in the Tourist Sector

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783662623077
  • Indbinding:
  • Paperback
  • Sideantal:
  • 221
  • Udgivet:
  • 20. september 2020
  • Udgave:
  • 12020
  • Størrelse:
  • 155x235x0 mm.
  • Vægt:
  • 454 g.
  • BLACK NOVEMBER
  Gratis fragt
Leveringstid: 8-11 hverdage
Forventet levering: 6. december 2024

Beskrivelse af Transactions on Large-Scale Data- and Knowledge-Centered Systems XLV

Interoperable Data Extraction and Analytics Queries over Blockchains.- Exploiting Twitter for Informativeness Classification in Disaster Situations.- COTILES: Leveraging Content and Structure for Evolutionary Community Detection.- A Weighted Feature-Based Image Quality Assessment Framework in Real-Time.- Sharing Knowledge in Digital Ecosystems Using Semantic Multimedia Big Data.- Facilitating and Managing Machine Learning and Data Analysis Tasks in Big Data Environments Using Web and Microservice Technologies.- Stable Marriage Matching for Homogenizing Load Distribution in a Cloud Data Center.- A Sentiment Analysis Software Framework for the Support of Business Information Architecture in the Tourist Sector

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