Observatorio de I+D+i UPM

Memorias de investigación
Ponencias en congresos:
An Ontology-Based Deep Learning Approach for Knowledge Graph Completion with Fresh Entities
Año:2019
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
Thispaperintroducesanewinitializationmethodforknowledgegraph (KG) embedding that can leverage ontological information in knowledge graph completion problems, such as link classification and link prediction. Although the initialization method is general and applicable to different KG embedding approaches in the literature, such as TransE or RESCAL, this paper experiments with deep learning and specifically with the neural tensor network (NTN) model. The experimental results show that the proposed method can improve link classification for a given relation by up to 15%. In a second contribution, the proposed method allows for addressing a problem not studied in the literature and introduced here as ?KG completion with fresh entities?. This is the use of KG embeddings for KG completion when one or several of the entities in a triple (head, relation, tail ) has not been observed in the training phase.
Internacional
Si
Nombre congreso
16th International Conference on Distributed Computing and Artificial Intelligence. DCAI 2019
Tipo de participación
960
Lugar del congreso
Ávila, España
Revisores
Si
ISBN o ISSN
978-3-030-23886-5
DOI
10.1007/978-3-030-23887-2_15
Fecha inicio congreso
26/06/2019
Fecha fin congreso
28/06/2019
Desde la página
125
Hasta la página
133
Título de las actas
Distributed Computing and Artificial Intelligence, 16th International Conference
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Elvira Amador Dominguez (UPM)
  • Autor: Patrick Hohenecker (Department of Computer Science, University of Oxford, Oxford, United Kingdom)
  • Autor: Thomas Lukasiewicz (Department of Computer Science, University of Oxford, Oxford, United Kingdom)
  • Autor: Daniel Manrique Gamo (UPM)
  • Autor: Emilio Serrano Fernandez (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Inteligencia Artificial (LIA)
  • Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial
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