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Titlebook: Linked Data Visualization; Techniques, Tools, a Laura Po,Nikos Bikakis,George Papastefanatos Book 2020 Springer Nature Switzerland AG 2020

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書目名稱Linked Data Visualization
副標題Techniques, Tools, a
編輯Laura Po,Nikos Bikakis,George Papastefanatos
視頻videohttp://file.papertrans.cn/587/586753/586753.mp4
叢書名稱Synthesis Lectures on Data, Semantics, and Knowledge
圖書封面Titlebook: Linked Data Visualization; Techniques, Tools, a Laura Po,Nikos Bikakis,George Papastefanatos Book 2020 Springer Nature Switzerland AG 2020
描述.Linked Data (LD) is a well-established standard for publishing and managing structured information on the Web, gathering and bridging together knowledge from different scientific and commercial domains. The development of Linked Data Visualization techniques and tools has been followed as the primary means for the analysis of this vast amount of information by data scientists, domain experts, business users, and citizens...This book covers a wide spectrum of visualization issues, providing an overview of the recent advances in this area, focusing on techniques, tools, and use cases of visualization and visual analysis of LD. It presents the basic concepts related to data visualization and the LD technologies, the techniques employed for data visualization based on the characteristics of data techniques for Big Data visualization, use tools and use cases in the LD context, and finally a thorough assessment of the usability of these tools under different scenarios...The purpose of this book is to offer a complete guide to the evolution of LD visualization for interested readers from any background and to empower them to get started with the visual analysis of such data. This book ca
出版日期Book 2020
版次1
doihttps://doi.org/10.1007/978-3-031-79490-2
isbn_ebook978-3-031-79490-2Series ISSN 2691-2023 Series E-ISSN 2691-2031
issn_series 2691-2023
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

書目名稱Linked Data Visualization影響因子(影響力)




書目名稱Linked Data Visualization影響因子(影響力)學科排名




書目名稱Linked Data Visualization網(wǎng)絡公開度




書目名稱Linked Data Visualization網(wǎng)絡公開度學科排名




書目名稱Linked Data Visualization被引頻次




書目名稱Linked Data Visualization被引頻次學科排名




書目名稱Linked Data Visualization年度引用




書目名稱Linked Data Visualization年度引用學科排名




書目名稱Linked Data Visualization讀者反饋




書目名稱Linked Data Visualization讀者反饋學科排名




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Springer Nature Switzerland AG 2020
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Laura Po,Nikos Bikakis,Federico Desimoni,George Papastefanatos isomorphism for a relation in the ordinary sense can be generalized to relationals. In section 9.2 we will see how this can be done. Given this notion of an isomorphism for a relational it is a straightforward matter to say what is meant by an automorphism for a relational. As a preliminary to the
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Introduction, publishing and interlinking structured data on the Web. Creating a connection between data and its contexts could lead to the development of intelligent search engines which could explore the Web, moving from a keyword-based approach to a meaning-based approach. Researches can be more accurate by e
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Visualization Use Cases,loring proprietary datasets. LD visualization is a particular task that differs from the classical data visualization since, usually, users do not have an a priori knowledge of the dataset and do not know if the dataset might be relevant for their goals. Visualizing LD means to handle several issues
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