Inproceedings3833
Entity Typing based on RDF2Vec using Supervised and Unsupervised Methods (Best Poster Award)
Entity Typing based on RDF2Vec using Supervised and Unsupervised Methods (Best Poster Award)
Published: 2020
Juni
Buchtitel: Proceedings of the 16th Extended Semantic Web Conference, P&D Track (ESWC 2020)
Ausgabe: 12124
Seiten: 203-207
Verlag: Springer
Organisation: Extended Semantic Web Conference
Referierte Veröffentlichung
BibTeX
Kurzfassung
Knowledge Graphs have been recognized as the foundation for diverse applications in the field of data mining, information retrieval, and natural language processing. So the completeness and the correctness of the KGs are of high importance. The type information of the entities in a KG, is one of the most vital facts. However, it has been observed that type information is often noisy or incomplete. In this work, the task of fine-grained entity typing is addressed by exploiting the pre-trained RDF2Vec vectors using supervised and unsupervised approaches.
Download: Media:Entity_Typing_based_on_RDF2Vec.pdf
Weitere Informationen unter: Link
DOI Link: 10.1007/978-3-030-62327-2_35
Information Service Engineering