Knowledge Graphs on the web - An overview

Heist, Nicolas ; Hertling, Sven ; Ringler, Daniel ; Paulheim, Heiko

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Document Type: Book chapter
Year of publication: 2020
Book title: Knowledge Graphs for eXplainable artificial intelligence : foundations, applications and challenges
The title of a journal, publication series: Studies on the Semantic Web
Volume: 47
Page range: 3-22
Publisher: Tiddi, Ilaria
Place of publication: Amsterdam; Heidelberg
Publishing house: IOS Press / AKA
ISBN: 978-1-64368-080-4 , 978-1-64368-081-1
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Publication language: English
Institution: School of Business Informatics and Mathematics > Data Science (Paulheim 2018-)
Subject: 004 Computer science, internet
Abstract: Knowledge Graphs are an emerging form of knowledge representation. While Google coined the term Knowledge Graph first and promoted it as a means to improve their search results, they are used in many applications today. In a knowledge graph, entities in the real world and/or a business domain (e.g., people, places, or events) are represented as nodes, which are connected by edges representing the relations between those entities. While companies such as Google, Microsoft, and Facebook have their own, non-public knowledge graphs, there is also a larger body of publicly available knowledge graphs, such as DBpedia or Wikidata. In this chapter, we provide an overview and comparison of those publicly available knowledge graphs, and give insights into their contents, size, coverage, and overlap.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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