Linked Data, Sakr

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: 121110.00 T
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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.

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: 55900.00 T
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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.

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: 170010.00 T
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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.

Автор: Nikolaos Konstantinou; Dimitrios-Emmanuel Spanos
Название: Materializing the Web of Linked Data
ISBN: 3319160737 ISBN-13(EAN): 9783319160733
Издательство: Springer
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Цена: 93160.00 T
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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.

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: 74530.00 T
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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.

Автор: Diana Trandab??; Daniela G?fu
Название: Linguistic Linked Open Data
ISBN: 3319329413 ISBN-13(EAN): 9783319329413
Издательство: Springer
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Цена: 46590.00 T
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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.

Автор: S?ren Auer; Volha Bryl; Sebastian Tramp
Название: Linked Open Data -- Creating Knowledge Out of Interlinked Data
ISBN: 3319098454 ISBN-13(EAN): 9783319098456
Издательство: Springer
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Цена: 44720.00 T
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Описание: 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. 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.

Название: Linked data and knowledge graph
ISBN: 3642540244 ISBN-13(EAN): 9783642540240
Издательство: Springer
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Цена: 52170.00 T
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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.

Автор: Diane Rasmussen Pennington, Louise Spiteri
Название: Social Tagging in a Linked Data Environment
ISBN: 1783303395 ISBN-13(EAN): 9781783303397
Издательство: Facet
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Цена: 218240.00 T
Наличие на складе: Невозможна поставка.
Описание: This book, representing researchers and practitioners across different information professions, will explore how social tags can link content across a variety of environments.

Автор: Pan Jeff Z., Vetere Guido, Gomez-Perez Jose Manuel
Название: Exploiting Linked Data and Knowledge Graphs in Large Organisations
ISBN: 3319833391 ISBN-13(EAN): 9783319833392
Издательство: Springer
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Цена: 158380.00 T
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Описание:

Part I Knowledge Graph Foundations & Architecture.- Part II Constructing, Understanding and Consuming Knowledge Graphs.- Part III Industrial Applications and Successful Stories.