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Titlebook: Relevant Query Answering over Streaming and Distributed Data; A Study for RDF Stre Shima Zahmatkesh,Emanuele Della Valle Book 2020 The Auth

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書目名稱Relevant Query Answering over Streaming and Distributed Data
副標(biāo)題A Study for RDF Stre
編輯Shima Zahmatkesh,Emanuele Della Valle
視頻videohttp://file.papertrans.cn/827/826321/826321.mp4
叢書名稱SpringerBriefs in Applied Sciences and Technology
圖書封面Titlebook: Relevant Query Answering over Streaming and Distributed Data; A Study for RDF Stre Shima Zahmatkesh,Emanuele Della Valle Book 2020 The Auth
描述.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..
出版日期Book 2020
關(guān)鍵詞Relevant Query Answering; Rank Aggregation; RSP Engine; Evolving Distributed Data; Streaming Data; Contin
版次1
doihttps://doi.org/10.1007/978-3-030-38339-8
isbn_softcover978-3-030-38338-1
isbn_ebook978-3-030-38339-8Series ISSN 2191-530X Series E-ISSN 2191-5318
issn_series 2191-530X
copyrightThe Author(s), under exclusive license to Springer Nature Switzerland AG 2020
The information of publication is updating

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Relevant Query Answering over Streaming and Distributed Data978-3-030-38339-8Series ISSN 2191-530X Series E-ISSN 2191-5318
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Background,emantic Web data and query model and a review of state-of-the-art works. Then, focusing on RDF Stream Processing, it presents the semantics of the RDF stream query language (RSP-QL), which is important for precisely formalize the problem in the following chapters. Then, the chapter proceeds to intro
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Handling Queries with a FILTER Clause,that joins streaming data with the distributed data, and contains a filter constrain on distributed data. In addition, it explains how to combine this policy with the one proposed in the previous chapter. Finally, a set of experimental evaluations shows how the proposed policies guarantee reactivene
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