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Link Prediction of Weighted Triples for Knowledge Graph Completion Within the Scholarly Domain

Knowledge graphs (KGs) are widely used for modeling scholarly communication, performing scientometric analyses, and supporting a variety of intelligent services to explore the literature and predict research dynamics. However, they often suffer from incompleteness (e.g., missing affiliations, refere...

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Principais autores: Mojtaba Nayyeri, Gokce Muge Cil, Sahar Vahdati, Francesco Osborne, Andrey Kravchenko, Simone Angioni, Angelo Salatino, Diego Reforgiato Recupero, Enrico Motta, Jens Lehmann
Formato: Artigo
Idioma:Inglês
Publicado em: IEEE 2021-01-01
coleção:IEEE Access
Assuntos:
Scholarly data
knowledge graphs
knowledge graph embeddings
loss functions
link prediction
scholarly communication
Acesso em linha:https://ieeexplore.ieee.org/document/9514834/
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