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Artículo
TAPON: a two-phase machine learning approach for semantic labelling
(Elsevier, 2019-01-01)
Through semantic labelling we enrich structured information from sources such as HTML pages, tables, or JSON files, with labels to integrate it into a local ontology. This process involves measuring some features of the ...
Artículo
An approach for discovering keywords from Spanish tweets using Wikipedia
(Universidad de Salamanca, 2015)
Most approaches to keywords discovery when analyzing microblogging messages (among them those from Twitter) are based on statistical and lexical information about the words that compose the text. The lack of context in ...
Artículo
TAPON-MT: a versatile framework for semantic labelling
(Elsevier, 2019-07)
Semantic labelling refers to the problem of assigning known labels to the elements of structured information from a source such as an HTML table or an RDF dump with unknown semantics. In the recent years it has become ...
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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 ...
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CAFE: Knowledge graph completion using neighborhood-aware features
(Elsevier, 2021)
Knowledge Graphs (KGs) currently contain a vast amount of structured information in the form of entities and relations. Because KGs are often constructed automatically by means of information extraction processes, they ...
Artículo
openSkies - Integration of Aviation Data into the R Ecosystem
(The R Foundation, 2021)
Aviation data has become increasingly more accessible to the public thanks to the adoption of technologies such as Automatic Dependent Surveillance-Broadcast (ADS-B) and Mode S, which provide aircraft information over ...
Artículo
A neural network for semantic labelling of structured information
(Elsevier, 2020-04-01)
Intelligent systems rely on rich sources of information to make informed decisions. Using information from external sources requires establishing correspondences between the information and known information classes. This ...
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 ...