Buscar
Mostrando ítems 1-6 de 6
Artículo
Artículo
Discovering and Analysing Ontological Models from Big RDF Data
(IGI Global, 2015)
The Web of Data, which comprises web sources that provide their data in RDF, is gaining popularity day after day. Ontological models over RDF data are shared and developed with the consensus of one or more communities. ...
Artículo
Multi-source dataset of e-commerce products with attributes for property matching
(Elsevier, 2022)
Schema/ontology matching consists in finding matches between types, properties and entities in heterogeneous sources of data in order to integrate them, which has become increasingly relevant with the development of web ...
Artículo
LEAPME: learning-based property matching with embeddings
(Elsevier, 2022)
Data integration tasks such as the creation and extension of knowledge graphs involve the fusion of heterogeneous entities from many sources. Matching and fusion of such entities require to also match and combine their ...
Artículo
Deep embeddings and Graph Neural Networks: using context to improve domain-independent predictions
(SprigerLink, 2023-06-28)
Graph neural networks (GNNs) are deep learning architectures that apply graph convolutions through message-passing processes between nodes, represented as embeddings. GNNs have recently become popular because of their ...
Artículo
LEAPME: Learning-based Property Matching with Embeddings
(Cornell University, 2020)
Data integration tasks such as the creation and extension of knowledge graphs involve the fusion of heterogeneous entities from many sources. Matching and fusion of such entities require to also match and combine their ...