Encyclopedia of Big Data Technologies

Living Edition
| Editors: Sherif Sakr, Albert Zomaya

Knowledge Graph Embeddings

  • Paolo Rosso
  • Dingqi Yang
  • Philippe Cudré-Mauroux
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-63962-8_284-1



Knowledge graph embeddings: a vector representation of entities and relations in a knowledge graph that preserves the inherent structure of the knowledge graph as well as the reasoning ability over the graph.


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...

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Paolo Rosso
    • 1
  • Dingqi Yang
    • 1
  • Philippe Cudré-Mauroux
    • 1
  1. 1.eXascale InfolabUniversity of FribourgFribourgSwitzerland

Section editors and affiliations

  • Philippe Cudré-Mauroux
    • 1
  • Olaf Hartig
    • 2
  1. 1.eXascale InfolabUniversity of FribourgFribourgSwitzerland
  2. 2.Linköping University