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Relevant Query Answering over Streaming and Distributed Data

A Study for RDF Streams and Evolving Web Data

Book
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Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Also part of the PoliMI SpringerBriefs book sub series (BRIEFSPOLIMI)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Shima Zahmatkesh, Emanuele Della Valle
    Pages 1-7
  3. Shima Zahmatkesh, Emanuele Della Valle
    Pages 9-25
  4. Shima Zahmatkesh, Emanuele Della Valle
    Pages 27-39
  5. Shima Zahmatkesh, Emanuele Della Valle
    Pages 41-54
  6. Shima Zahmatkesh, Emanuele Della Valle
    Pages 55-73
  7. Shima Zahmatkesh, Emanuele Della Valle
    Pages 75-114
  8. Shima Zahmatkesh, Emanuele Della Valle
    Pages 115-119
  9. Back Matter
    Pages 121-123

About this book

Introduction

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.

Keywords

Relevant Query Answering Rank Aggregation RSP Engine Evolving Distributed Data Streaming Data Continuous Query Big Data

Authors and affiliations

  1. 1.DEIBPolitecnico di MilanoMilanoItaly
  2. 2.DEIBPolitecnico di MilanoMilanoItaly

Bibliographic information

  • Book Title Relevant Query Answering over Streaming and Distributed Data
  • Book Subtitle A Study for RDF Streams and Evolving Web Data
  • Authors Shima Zahmatkesh
    Emanuele Della Valle
  • Series Title SpringerBriefs in Applied Sciences and Technology
  • Series Abbreviated Title SpringerBriefs in Applied Sciences
  • DOI https://doi.org/10.1007/978-3-030-38339-8
  • Copyright Information The Author(s), under exclusive license to Springer Nature Switzerland AG 2020
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Softcover ISBN 978-3-030-38338-1
  • eBook ISBN 978-3-030-38339-8
  • Series ISSN 2191-530X
  • Series E-ISSN 2191-5318
  • Edition Number 1
  • Number of Pages IX, 123
  • Number of Illustrations 32 b/w illustrations, 1 illustrations in colour
  • Topics Database Management
    Data Engineering
    Big Data
  • Buy this book on publisher's site
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