Knowledge graph embeddings

Rosso, Paolo; Yang, Dingqi; Cudré-Mauroux, Philippe

doi:10.1007/978-3-319-63962-8_284-1

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Book chapter

Knowledge graph embeddings

Université de Fribourg

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