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Materializing the Web of Linked Data, Nikolaos Konstantinou; Dimitrios-Emmanuel Spanos


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Автор: Nikolaos Konstantinou; Dimitrios-Emmanuel Spanos
Название:  Materializing the Web of Linked Data
ISBN: 9783319160733
Издательство: Springer
Классификация:


ISBN-10: 3319160737
Обложка/Формат: Hardcover
Страницы: 133
Вес: 0.39 кг.
Дата издания: 21.04.2015
Язык: English
Издание: 2015 ed.
Иллюстрации: 7 tables, black and white; 28 illustrations, black and white; xiv, 133 p. 28 illus.
Размер: 234 x 156 x 10
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book explains the Linked Data domain by adopting a bottom-up approach: it introduces the fundamental Semantic Web technologies and building blocks, which are then combined into methodologies and end-to-end examples for publishing datasets as Linked Data, and use cases that harness scholarly information and sensor data.


Cases On Open-Linked Data And Semantic Web Applications

Автор: Ord??ez De Pablos, Lytras, Tenny
Название: Cases On Open-Linked Data And Semantic Web Applications
ISBN: 1466628278 ISBN-13(EAN): 9781466628274
Издательство: Mare Nostrum (Eurospan)
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Цена: 25502.00 р.
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Описание: With the purpose of building upon standard web technologies, open linked data serves as a useful way to connect previously unrelated data and to publish structured data on the web. The application of these elements leads to the creation of data commons called semantic web. <br><br><em>Cases on Open-Linked Data and Semantic Web Applications</em> brings together new theories, research findings and case studies which cover the recent developments and approaches towards applied open linked data and semantic web in the context of information systems. By enhancing the understanding of open linked data in business, science and information technologies, this reference source aims to be useful for academics, researchers, and practitioners. With the purpose of building upon standard web technologies, open linked data serves as a useful way to connect previously unrelated data and to publish structured data on the web. The application of these elements leads to the creation of data commons called semantic web.

Exploiting Linked Data and Knowledge Graphs for Large Organisations

Автор: Jeff Z. Pan; Guido Vetere; Jose Manuel Gomez-Perez
Название: Exploiting Linked Data and Knowledge Graphs for Large Organisations
ISBN: 3319456520 ISBN-13(EAN): 9783319456522
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book addresses the topic of exploiting enterprise-linked data with a particular focus on knowledge construction and accessibility within enterprises. It identifies the gaps between the requirements of enterprise knowledge consumption and "standard" data consuming technologies by analysing real-world use cases, and proposes the enterprise knowledge graph to fill such gaps.

It provides concrete guidelines for effectively deploying linked-data graphs within and across business organizations. It is divided into three parts, focusing on the key technologies for constructing, understanding and employing knowledge graphs. Part 1 introduces basic background information and technologies, and presents a simple architecture to elucidate the main phases and tasks required during the lifecycle of knowledge graphs. Part 2 focuses on technical aspects; it starts with state-of-the art knowledge-graph construction approaches, and then discusses exploration and exploitation techniques as well as advanced question-answering topics concerning knowledge graphs. Lastly, Part 3 demonstrates examples of successful knowledge graph applications in the media industry, healthcare and cultural heritage, and offers conclusions and future visions.

Linked data and knowledge graph

Название: Linked data and knowledge graph
ISBN: 3642540244 ISBN-13(EAN): 9783642540240
Издательство: Springer
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Цена: 7826.00 р.
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Описание: This book constitutes the refereed proceedings of the Seventh Chinese Semantic Web Symposium and the Second Chinese Web Science Conference, CSWS 2013, held in Shanghai, China in August 2013. The 14 revised full papers presented together with 6 short papers and 3 poster papers were carefully reviewed and selected from 48 submissions.

Materializing the Web of Linked Data

Автор: Nikolaos Konstantinou; Dimitrios-Emmanuel Spanos
Название: Materializing the Web of Linked Data
ISBN: 331935745X ISBN-13(EAN): 9783319357454
Издательство: Springer
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Цена: 11179.00 р.
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Описание: This book explains the Linked Data domain by adopting a bottom-up approach: it introduces the fundamental Semantic Web technologies and building blocks, which are then combined into methodologies and end-to-end examples for publishing datasets as Linked Data, and use cases that harness scholarly information and sensor data.

Linked Data in Linguistics

Автор: Christian Chiarcos; Sebastian Nordhoff; Sebastian
Название: Linked Data in Linguistics
ISBN: 3642434967 ISBN-13(EAN): 9783642434969
Издательство: Springer
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Цена: 13275.00 р.
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Описание: The contributions assembled in this volume illustrate the band-width of applications of the Linked Data paradigm for representative types of language resources. They cover lexical-semantic resources, annotated corpora, typological databases as well as terminology and metadata repositories.

Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data

Автор: Chen
Название: Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data
ISBN: 9811031673 ISBN-13(EAN): 9789811031670
Издательство: Springer
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Цена: 8385.00 р.
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Описание: This book constitutes the refereed proceedings of the first China Conference on Knowledge Graph and Semantic Computing, CCKS, held in Beijing, China, in September 2016.The 19 revised full papers presented together with 6 shared tasks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on knowledge representation and learning; knowledge graph construction and information extraction; linked data and knowledge-based systems; shared tasks.

Linguistic Linked Open Data

Автор: Diana Trandab??; Daniela G?fu
Название: Linguistic Linked Open Data
ISBN: 3319329413 ISBN-13(EAN): 9783319329413
Издательство: Springer
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Цена: 6988.00 р.
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Описание: Ontological modeling of social media data.- Application of social media and linked data methodologies in real-life scenarios.- User proling and assessing the suitability of content from social media.- Extracting and linking content.- Sentiment analysis in social media and linked data.-Social data mining to create structured social media resources.


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