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Domain-Specific Knowledge Graph Construction (SpringerBriefs in Computer Science) - Tapa blanda

Libro 289 de 322: SpringerBriefs in Computer Science

Kejriwal, Mayank

 
9783030123741: Domain-Specific Knowledge Graph Construction (SpringerBriefs in Computer Science)
Tapa blanda
ISBN 10: 303012374X ISBN 13: 9783030123741
Editorial: Springer, 2019

Sinopsis

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 an accessible 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.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Mayank Kejriwal holds joint appointments as a Research Assistant Professor and Research Team Leader at the University of Southern California. His research in artificial intelligence and complex systems has been funded by corporations, the Department of Defense, and private foundations, and has been published in numerous journals and conference proceedings. He is the co-author of three books, including a definitive textbook on knowledge graphs, a frontier area of AI research.

De la contraportada

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 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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2019
Idioma
Inglés
ISBN 10 
303012374X
ISBN 13 
9783030123741
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
107
Contacto del fabricante
ProductSafety@springernature.com
ProductSafety@springernature.com

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