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Adaptive Computation and Machine Learning
Knowledge Graphs: Fundamentals, Techniques, and Applications
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.
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.
- GenresScience
568 pages, Hardcover
Published March 30, 2021
40 people are currently reading
90 people want to read
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Displaying 1 - 2 of 2 reviews
February 21, 2024
Has a tendency to throw up figures containing terminology or concepts that haven't been defined yet, which can be confusing.
Also uses some terms in contradiction to the definitions they provide. For example, they first define "foaf" to mean "Friend of a Friend," but then go on to use "foaf" for all kinds of relations that are not between friends, e.g. "isi:mayank_kijriwal" --foaf:name-->"Mayank Kejriwal". (And it throws up a URL for "foaf" when no such URLs have been mentioned.)
In some respects, this book could be a good refresher who those who are already familiar with the material by other means, but a reader new to the topic, this inconsistency of terminology and the tendency to things to with no prior explanation makes for a choppy experience.
Another serious issue is that the book is exclusively focussed on web-based knowledge. So after slogging through Chapter 2 about RDF, one finds that the chapter on "Domain Discovery" concerns *only* trawling the web. There is absolutely nothing about conducting interviews of organizations or individuals to obtain and represent their knowledge.
Also uses some terms in contradiction to the definitions they provide. For example, they first define "foaf" to mean "Friend of a Friend," but then go on to use "foaf" for all kinds of relations that are not between friends, e.g. "isi:mayank_kijriwal" --foaf:name-->"Mayank Kejriwal". (And it throws up a URL for "foaf" when no such URLs have been mentioned.)
In some respects, this book could be a good refresher who those who are already familiar with the material by other means, but a reader new to the topic, this inconsistency of terminology and the tendency to things to with no prior explanation makes for a choppy experience.
Another serious issue is that the book is exclusively focussed on web-based knowledge. So after slogging through Chapter 2 about RDF, one finds that the chapter on "Domain Discovery" concerns *only* trawling the web. There is absolutely nothing about conducting interviews of organizations or individuals to obtain and represent their knowledge.
Displaying 1 - 2 of 2 reviews