Knowledge graphs

by Hogan, Aidan

Type Book

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Title Statements

Full title :Knowledge graphs / Aidan Hogan, Eva Blomqvist, Michael Cochez [and 15 others].

Summary

This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques--based on statistics, graph analytics, machine learning, etc.--can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.

Edition Statements

Publication Date:©2022

Publication Statements

Publisher(s):Morgan & Claypool Publishers
Place of Publication:S.l
Language:eng
Publication Date:©2022

The Physical Object

Description:xix, 237 pages : illustrations ; : 23 cm

Edition Identifiers

ISBN:1636392377, 9781636392370, 1636392350, 9781636392356
oclc:on1286422705
LC Classification:QA76.9.I52
Dewey Decimal:001.4/226

1. Introduction -- 2. Data graphs -- 2.1. Models -- 2.2. Querying

3. Schema, identity, and context -- 3.1. Schema -- 3.2. Identity -- 3.3. Context

4. Deductive knowledge -- 4.1. Ontologies -- 4.2. Reasoning

5. Inductive knowledge -- 5.1. Graph analytics -- 5.2. Knowledge graph embeddings -- 5.3. Graph neural networks -- 5.4. Symbolic learning

6. Creation and enrichment -- 6.1. Human collaboration -- 6.2. Text sources -- 6.3. Markup sources -- 6.4. Structured sources -- 6.5. Schema/ontology creation

7. Quality assessment -- 7.1. Accuracy -- 7.2. Coverage -- 7.3. Coherency -- 7.4. Succinctness -- 7.5. Other quality dimensions

8. Refinement -- 8.1. Completion -- 8.2. Correction -- 8.3. Other refinement tasks

9. Publication -- 9.1. Best practices -- 9.2. Access protocols -- 9.3. Usage control

10. Knowledge graphs in practice -- 10.1. Open knowledge graphs -- 10.2. Enterprise knowledge graphs -- 11. Conclusions.

Subjects

Conceptual structures (Information theo… Graphic methods Graphic methods -- Computer programs Graphs Information visualization Informatique sémantique Méthodes graphiques Semantic computing Structures conceptuelles Visualisation de l'information