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Relevant Query Answering over Streaming and Distributed Data [electronic resource] : A Study for RDF Streams and Evolving Web Data /

By: Contributor(s): Material type: TextTextSeries: PoliMI SpringerBriefsPublisher: Cham : Springer International Publishing : Imprint: Springer, 2020Edition: 1st ed. 2020Description: IX, 123 p. 33 illus., 1 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783030383398
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 005.74 23
LOC classification:
  • QA76.9.D3
Online resources: In: Springer Nature eBookSummary: This book examines the problem of relevant query answering over the Web and provides a comprehensive overview of relevant query answering over streaming and distributed data. In recent years, Web applications that combine highly dynamic data streams with data distributed over the Web to provide relevant answers have attracted increasing attention. Answering in a timely fashion, i.e., reactively, is one of the most important performance indicators, especially when the distributed data is evolving. The book proposes a solution that retains a local replica of the distributed data and offers various maintenance policies to refresh the replica over time. A limited refresh budget guarantees the reactiveness of the system. Focusing on stream processing and Semantic Web, it appeals to scientists and graduate students in the field.
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This book examines the problem of relevant query answering over the Web and provides a comprehensive overview of relevant query answering over streaming and distributed data. In recent years, Web applications that combine highly dynamic data streams with data distributed over the Web to provide relevant answers have attracted increasing attention. Answering in a timely fashion, i.e., reactively, is one of the most important performance indicators, especially when the distributed data is evolving. The book proposes a solution that retains a local replica of the distributed data and offers various maintenance policies to refresh the replica over time. A limited refresh budget guarantees the reactiveness of the system. Focusing on stream processing and Semantic Web, it appeals to scientists and graduate students in the field.

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