Knowledge Graphs: Fundamentals, Techniques, and Applications
| AUTHOR | Knoblock, Craig A.; Kejriwal, Mayank; Szekely, Pedro et al. |
| PUBLISHER | MIT Press (03/30/2021) |
| PRODUCT TYPE | Hardcover (Hardcover) |
Description
A rigorous and comprehensive textbook covering the major approaches to knowledge graphs, an active and interdisciplinary area within artificial intelligence. The field of knowledge graphs, which allows us to model, process, and derive insights from complex real-world data, has emerged as an active and interdisciplinary area of artificial intelligence over the last decade, drawing on such fields as natural language processing, data mining, and the semantic web. Current projects involve predicting cyberattacks, recommending products, and even gleaning insights from thousands of papers on COVID-19. This textbook offers rigorous and comprehensive coverage of the field. It focuses systematically on the major approaches, both those that have stood the test of time and the latest deep learning methods.
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Product Format
Product Details
ISBN-13:
9780262045094
ISBN-10:
0262045095
Binding:
Hardback or Cased Book (Sewn)
Content Language:
English
More Product Details
Page Count:
568
Carton Quantity:
14
Product Dimensions:
7.20 x 1.20 x 9.10 inches
Weight:
2.30 pound(s)
Feature Codes:
Bibliography,
Index,
Price on Product,
Illustrated
Country of Origin:
US
Subject Information
BISAC Categories
Computers | Artificial Intelligence - General
Computers | Database Administration & Management
Computers | Data Science - Data Visualization
Dewey Decimal:
001.422
Library of Congress Control Number:
2020028169
Descriptions, Reviews, Etc.
publisher marketing
A rigorous and comprehensive textbook covering the major approaches to knowledge graphs, an active and interdisciplinary area within artificial intelligence. The field of knowledge graphs, which allows us to model, process, and derive insights from complex real-world data, has emerged as an active and interdisciplinary area of artificial intelligence over the last decade, drawing on such fields as natural language processing, data mining, and the semantic web. Current projects involve predicting cyberattacks, recommending products, and even gleaning insights from thousands of papers on COVID-19. This textbook offers rigorous and comprehensive coverage of the field. It focuses systematically on the major approaches, both those that have stood the test of time and the latest deep learning methods.
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Your Price
$54.45