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Linked Data, Hart, Glen , Dolbear, Catherine


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Цена: 8879.00р.
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Автор: Hart, Glen , Dolbear, Catherine
Название:  Linked Data
ISBN: 9780367866549
Издательство: Taylor&Francis
Классификация:



ISBN-10: 0367866544
Обложка/Формат: Paperback
Страницы: 292
Вес: 0.83 кг.
Дата издания: 31.03.2020
Язык: English
Размер: 234 x 156 x 16
Читательская аудитория: Tertiary education (us: college)
Основная тема: Data Preparation & Mining
Подзаголовок: A Geographic Perspective
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание: Linked Data opens up structured data from databases to be searched and queried via the web, and a geographic element is increasingly being used to link to those data. This book helps you understand how to organize and describe data that includes geographic content and how to publish it as Linked Data for the Semantic Web, as well as explaining t


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.

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.

Exploiting Linked Data and Knowledge Graphs in Large Organisations

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: 23757.00 р.
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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.

Linked Data

Автор: Sakr
Название: Linked Data
ISBN: 3319735144 ISBN-13(EAN): 9783319735146
Издательство: Springer
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Цена: 22359.00 р.
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Описание:

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 for RDF 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 insights into some of the open challenges and research directions.

Providing an updated overview of methods, technologies and systems related to Linked Data this book is mainly intended for students and researchers who are interested in the Linked Data domain. It enables students to gain an understanding of the foundations and underpinning technologies and standards for Linked Data, while researchers benefit from the in-depth coverage of the emerging and ongoing advances in Linked Data storing, querying, reasoning, and provenance management systems. Further, it serves as a starting point to tackle the next research challenges in the domain of Linked Data management.
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.

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.

Materializing the Web of Linked Data

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: 13974.00 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.

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.


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