
Knowledge Graphs: Fundamentals, Techniques, and Applications
(Adaptive Computation and Machine Learning series)
Author(s): Mayank Kejriwal (Author), Craig A. Knoblock (Author), Pedro Szekely (Author)
- Publisher Finelybook 出版社: The MIT Press
- Publication Date 出版日期: March 30, 2021
- Language 语言: English
- Print length 页数: 568 pages
- ISBN-10: 0262045095
- ISBN-13: 9780262045094
Book Description
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.
Editorial Reviews
Editorial Reviews
Review
—Pascal Hitzler, Lloyd T. Smith Creativity in Engineering Chair,Department of Computer Science, Kansas State University; Director of the Center for Artificial Intelligence and Data Science (CAIDS)
“A comprehensive and thorough guide covering every aspect of building and using knowledge graphs. Read the book and learn everything that you need to know to apply knowledge graphs in practice.”
—Natasha Noy, Research Scientist, Google
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