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Titlebook: Linked Open Data -- Creating Knowledge Out of Interlinked Data; Results of the LOD2 S?ren Auer,Volha Bryl,Sebastian Tramp Book‘‘‘‘‘‘‘‘ 201

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書(shū)目名稱(chēng)Linked Open Data -- Creating Knowledge Out of Interlinked Data
副標(biāo)題Results of the LOD2
編輯S?ren Auer,Volha Bryl,Sebastian Tramp
視頻videohttp://file.papertrans.cn/587/586761/586761.mp4
概述Provides an overview on some key aspects of the emerging field of Linked Data.Describes a diverse number of research, technology and application advances and refers the reader to further detailed tech
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Linked Open Data -- Creating Knowledge Out of Interlinked Data; Results of the LOD2 S?ren Auer,Volha Bryl,Sebastian Tramp Book‘‘‘‘‘‘‘‘ 201
描述Linked Open Data (LOD) is a pragmatic approach for realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system. This book presents an overview on the results of the research project “LOD2 -- Creating Knowledge out of Interlinked Data”. LOD2 is a large-scale integrating project co-funded by the European Commission within the FP7 Information and Communication Technologies Work Program. Commencing in September 2010, this 4-year project comprised leading Linked Open Data research groups, companies, and service providers from across 11 European countries and South Korea. The aim of this project was to advance the state-of-the-art in research and development in four key areas relevant for Linked Data, namely 1. RDF data management; 2. the extraction, creation, and enrichment of structured RDF data; 3. the interlinking and fusion of Linked Data from different sources and 4. the authoring, exploration and visualization of Linked Data.
出版日期Book‘‘‘‘‘‘‘‘ 2014
關(guān)鍵詞DBpedia; LOD; RDF; SPARQL; data authoring; data enrichment; data exploration; data extraction; data integrat
版次1
doihttps://doi.org/10.1007/978-3-319-09846-3
isbn_softcover978-3-319-09845-6
isbn_ebook978-3-319-09846-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and the Author(s) 2014
The information of publication is updating

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Advances in Large-Scale RDF Data Management which leads to more join effort than needed in SQL systems. In this chapter, we first discuss the new column store techniques applied to Virtuoso, the enhancements in its cluster parallel version, and show its performance using the popular BSBM benchmark at the unsurpassed scale of 150?billion trip
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Knowledge Base Creation, Enrichment and Repairowledge bases. However, schema information is needed for consistency checking and finding modelling problems. We will present a combination of enrichment and repair steps to tackle this problem based on previous research in machine learning and knowledge representation. Overall, the Chapter describe
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0302-9743 red RDF data; 3. the interlinking and fusion of Linked Data from different sources and 4. the authoring, exploration and visualization of Linked Data.978-3-319-09845-6978-3-319-09846-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Volha Bryl,Christian Bizer,Robert Isele,Mateja Verlic,Soon Gill Hong,Sammy Jang,Mun Yong Yi,Key-Sun
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