Domain Specific Knowledge Graph Construction by Kejriwal Mayank (21 results)
Language: English
Published by Springer, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
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Published by Springer, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
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Language: English
Published by Springer, 2019
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Language: English
Published by Springer, 2019
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Language: English
Published by Springer Nature Switzerland AG, CH, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
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Paperback. Condition: New. 2019 ed. The vast amounts of ontologically unstructured information on the Web, including HTML, XML and JSON documents, natural language documents, tweets, blogs, markups, and even structured documents like CSV tables, all contain useful knowledge that can present a tremendous advantage to the Artifici…al Intelligence community if extracted robustly, efficiently and semi-automatically as knowledge graphs. Domain-specific Knowledge Graph Construction (KGC) is an active research area that has recently witnessed impressive advances due to machine learning techniques like deep neural networks and word embeddings. This book will synthesize Knowledge Graph Construction over Web Data in an engaging and accessible manner. The book describes a timely topic for both early -and mid-career researchers. Every year, more papers continue to be published on knowledge graph construction, especially for difficult Web domains. This book serves as a useful reference, as well as anaccessible but rigorous overview of this body of work. The book presents interdisciplinary connections when possible to engage researchers looking for new ideas or synergies. The book also appeals to practitioners in industry and data scientists since it has chapters on both data collection, as well as a chapter on querying and off-the-shelf implementations.
Language: English
Published by Springer, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
- Softcover
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Language: English
Published by Springer 2019-03-15, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
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Language: English
Published by Springer, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
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Language: English
Published by Springer, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
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Language: English
Published by Springer, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
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Language: English
Published by Springer-Verlag New York Inc, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
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Language: English
Published by Springer International Publishing, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
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Condition: New. The book describes a timely topic for both early -and mid-career researchers. Every year, more papers continue to be published on knowledge graph construction, especially for difficult Web domains. This work serves as a useful reference, as we.
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Published by Springer, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
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Taschenbuch. Condition: Neu. Domain-Specific Knowledge Graph Construction | Mayank Kejriwal | Taschenbuch | SpringerBriefs in Computer Science | xiv | Englisch | 2019 | Springer | EAN 9783030123741 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot…]com | Anbieter: preigu.
Language: English
Published by Springer, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
- Softcover
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The vast amounts of ontologically unstructured information on the Web, including HTML, XML and JSON documents, natural language documents, tweets, blogs, markups, and even structured documents like CSV tables, all contain useful knowledge that can…present a tremendous advantage to the Artificial Intelligence community if extracted robustly, efficiently and semi-automatically as knowledge graphs. Domain-specific Knowledge Graph Construction (KGC) is an active research area that has recently witnessed impressive advances due to machine learning techniques like deep neural networks and word embeddings. This book will synthesize Knowledge Graph Construction over Web Data in an engaging and accessible manner. The book describes a timely topic for both early -and mid-career researchers. Every year, more papers continue to be published on knowledge graph construction, especially for difficult Web domains. This book serves as a useful reference, as well as anaccessible but rigorous overview of this body of work. The book presentsinterdisciplinary connections when possible to engage researchers looking for new ideas or synergies.The book also appeals to practitioners in industry and data scientists since it has chapters on both data collection, as well as a chapter on querying and off-the-shelf implementations.
Language: English
Published by Springer Nature Switzerland AG, CH, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
- Softcover
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Paperback. Condition: New. 2019 ed. The vast amounts of ontologically unstructured information on the Web, including HTML, XML and JSON documents, natural language documents, tweets, blogs, markups, and even structured documents like CSV tables, all contain useful knowledge that can present a tremendous advantage to the Artifici…al Intelligence community if extracted robustly, efficiently and semi-automatically as knowledge graphs. Domain-specific Knowledge Graph Construction (KGC) is an active research area that has recently witnessed impressive advances due to machine learning techniques like deep neural networks and word embeddings. This book will synthesize Knowledge Graph Construction over Web Data in an engaging and accessible manner. The book describes a timely topic for both early -and mid-career researchers. Every year, more papers continue to be published on knowledge graph construction, especially for difficult Web domains. This book serves as a useful reference, as well as anaccessible but rigorous overview of this body of work. The book presents interdisciplinary connections when possible to engage researchers looking for new ideas or synergies. The book also appeals to practitioners in industry and data scientists since it has chapters on both data collection, as well as a chapter on querying and off-the-shelf implementations.
Language: English
Published by Springer, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
- Softcover
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Language: English
Published by Springer-Verlag New York Inc, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
- Softcover
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Paperback. Condition: Brand New. 107 pages. 9.00x6.00x0.25 inches. In Stock. This item is printed on demand.
Language: English
Published by Springer International Publishing, Springer Nature Switzerland Mär 2019, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The vast amounts of ontologically unstructured information on the Web, including HTML, XML and JSON documents, natural language documents, tweets, blogs, markups, and even structured documents like CSV tables, all contain useful kno…wledge that can present a tremendous advantage to the Artificial Intelligence community if extracted robustly, efficiently and semi-automatically as knowledge graphs. Domain-specific Knowledge Graph Construction (KGC) is an active research area that has recently witnessed impressive advances due to machine learning techniques like deep neural networks and word embeddings. This book will synthesize Knowledge Graph Construction over Web Data in an engaging and accessible manner. The book describes a timely topic for both early -and mid-career researchers. Every year, more papers continue to be published on knowledge graph construction, especially for difficult Web domains. This book serves as a useful reference, as well as anaccessible but rigorous overview of this body of work. The book presentsinterdisciplinary connections when possible to engage researchers looking for new ideas or synergies.The book also appeals to practitioners in industry and data scientists since it has chapters on both data collection, as well as a chapter on querying and off-the-shelf implementations. 124 pp. Englisch.
Language: English
Published by Springer, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
- Softcover
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Language: English
Published by Springer, 2019
Series: Book 289 of 322 - SpringerBriefs in Computer Science
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Language: English
Published by Springer, Springer International Publishing Mär 2019, 2019
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The vast amounts of ontologically unstructured information on the Web, including HTML, XML and JSON documents, natural language documents, tweets, blogs, markups, and even structured documents like CSV tables, all contain useful knowled…ge that can present a tremendous advantage to the Artificial Intelligence community if extracted robustly, efficiently and semi-automatically as knowledge graphs. Domain-specific Knowledge Graph Construction (KGC) is an active research area that has recently witnessed impressive advances due to machine learning techniques like deep neural networks and word embeddings. This book will synthesize Knowledge Graph Construction over Web Data in an engaging and accessible manner.The book describes a timely topic for both early -and mid-career researchers. Every year, more papers continue to be published on knowledge graph construction, especially for difficult Web domains. This book serves as a useful reference, as well as anaccessible but rigorous overview of this body of work. The book presents interdisciplinary connections when possible to engage researchers looking for new ideas or synergies. The book also appeals to practitioners in industry and data scientists since it has chapters on both data collection, as well as a chapter on querying and off-the-shelf implementations.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 124 pp. Englisch.
