Knowledge graph embeddings
- Rosso, Paolo eXascale Infolab, University of Fribourg, Switzerland
- Yang, Dingqi eXascale Infolab, University of Fribourg, Switzerland
- Cudré-Mauroux, Philippe eXascale Infolab, University of Fribourg, Switzerland
-
2018
Published in:
- Encyclopedia of Big Data Technologies. - 2018, p. 1–7
English
With the growing popularity of multi-relational data on the Web, knowledge graphs (KGs) have become a key data source in various application domains, such as Web search, question answering, and natural language understanding. In a typical KG such as Freebase (Bollacker et al. 2008) or Google’s Knowledge Graph (Google 2014), entities are connected via relations. For example, Bern is capital of Switzerland. Formally, a popular approach to represent such relational data is to use the Resource Description Framework. It defines a fact as a triple (subject, predicate, and object), which is also known as head, relation, and tail or (h, r, t) for short. Following the above example, the head, relation, and tail...
- Faculty
- Faculté des sciences et de médecine
- Department
- Département d'Informatique
- Language
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- English
- Classification
- Computer science and technology
- License
- License undefined
- Identifiers
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- RERO DOC 324401
- DOI 10.1007/978-3-319-63962-8_284-1
- Persistent URL
- https://folia.unifr.ch/unifr/documents/307732
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