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Titlebook: Linked Data; Storing, Querying, a Sherif Sakr,Marcin Wylot,Irini Fundulaki Book 2018 Springer International Publishing AG 2018 Database Des

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發(fā)表于 2025-3-21 19:00:05 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Linked Data
副標(biāo)題Storing, Querying, a
編輯Sherif Sakr,Marcin Wylot,Irini Fundulaki
視頻videohttp://file.papertrans.cn/587/586751/586751.mp4
概述Provides a comprehensive overview of the state-of-the-art in storing, querying, reasoning and data provenance aspects of Linked Data.Describes in detail the processing of and reasoning about dynamic,
圖書(shū)封面Titlebook: Linked Data; Storing, Querying, a Sherif Sakr,Marcin Wylot,Irini Fundulaki Book 2018 Springer International Publishing AG 2018 Database Des
描述This book describes efficient and effective techniques for harnessing the power of Linked Data by tackling the various aspects of managing its growing volume: storing, querying, reasoning, provenance management and benchmarking..To this end, Chapter 1 introduces the main concepts of the Semantic Web and Linked Data and provides a roadmap for the book. Next, Chapter 2 briefly presents the basic concepts underpinning Linked Data technologies that are discussed in the book. Chapter 3 then offers an overview of various techniques and systems for centrally querying RDF datasets, and Chapter 4 outlines various techniques and systems for efficiently querying large RDF datasets in distributed environments. Subsequently, Chapter 5 explores how streaming requirements are addressed in current, state-of-the-art RDF stream data processing. Chapter 6 covers performance and scaling issues of distributed RDF reasoning systems, while Chapter 7 details benchmarks forRDF query engines and instance matching systems. Chapter 8 addresses the provenance management for Linked Data and presents the different provenance models developed. Lastly, Chapter 9 offers a brief summary, highlighting and providing i
出版日期Book 2018
關(guān)鍵詞Database Design and Models; Semi-structured Data; Query Languages; RDF; Information Integration; Semantic
版次1
doihttps://doi.org/10.1007/978-3-319-73515-3
isbn_softcover978-3-030-08803-3
isbn_ebook978-3-319-73515-3
copyrightSpringer International Publishing AG 2018
The information of publication is updating

書(shū)目名稱(chēng)Linked Data影響因子(影響力)




書(shū)目名稱(chēng)Linked Data影響因子(影響力)學(xué)科排名




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書(shū)目名稱(chēng)Linked Data網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Linked Data被引頻次




書(shū)目名稱(chēng)Linked Data被引頻次學(xué)科排名




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書(shū)目名稱(chēng)Linked Data讀者反饋學(xué)科排名




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Distributed Reasoning of RDF Data,e.g., Hadoop, Spark). In this chapter, we cover five main categories of distributed RDF reasoning systems: (1) Peer-to-Peer RDF reasoning systems, (2) NoSQL-based RDF reasoning systems, (3) Hadoop-based RDF reasoning systems, (4) Spark-based RDF reasoning systems, and (5) shared memory RDF reasoning systems.
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Benchmarking RDF Query Engines and Instance Matching Systems, are used to inform users of the strengths and weaknesses of competing tools and approaches, but more importantly, they encourage the advancement of technology by providing both academia and industry with clear targets for performance and functionality.
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Fundamentals,conventional Web, the SemanticWeb aims to interconnect these data so that all datasets contribute to a global data integration, connecting data from diverse domains and sources. In practice, all concepts underpinning Linked Data are standardized by the World Wide Web Consortium. The Consortium publi
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