Relevant Query Answering over Streaming and Distributed Data : A Study for RDF Streams and Evolving Web Data

Emanuele Della Valle

ISBN 10: 3030383385 / ISBN 13: 9783030383381

Published by Springer International Publishing, Springer International Publishing, 2020

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783030383381

Bibliographic Details

• Title: Relevant Query Answering over Streaming and Distributed Data : A Study for RDF Streams and Evolving Web Data
• Publisher: Springer International Publishing, Springer International Publishing
• Publication Date: 2020
• Language: English
• ISBN 10: 3030383385
• ISBN 13: 9783030383381
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 8D millimeters 235 millimeters width by 155 millimeters height by 8 millimeters depth
• Weight: 219 grams

About this title

Synopsis

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.