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pro vyhledávání: '"Pesquita, Cátia"'
Knowledge Graphs (KG) are the backbone of many data-intensive applications since they can represent data coupled with its meaning and context. Aligning KGs across different domains and providers is necessary to afford a fuller and integrated represen
Externí odkaz:
http://arxiv.org/abs/2310.07417
Autor:
Chen, Jiaoyan, Dong, Hang, Hastings, Janna, Jiménez-Ruiz, Ernesto, López, Vanessa, Monnin, Pierre, Pesquita, Catia, Škoda, Petr, Tamma, Valentina
The term life sciences refers to the disciplines that study living organisms and life processes, and include chemistry, biology, medicine, and a range of other related disciplines. Research efforts in life sciences are heavily data-driven, as they pr
Externí odkaz:
http://arxiv.org/abs/2309.17255
A knowledge graph is a powerful representation of real-world entities and their relations. The vast majority of these relations are defined as positive statements, but the importance of negative statements is increasingly recognized, especially under
Externí odkaz:
http://arxiv.org/abs/2308.03447
Publikováno v:
International Conference on Principles of Knowledge Representation and Reasoning 2023
Knowledge graphs represent facts about real-world entities. Most of these facts are defined as positive statements. The negative statements are scarce but highly relevant under the open-world assumption. Furthermore, they have been demonstrated to im
Externí odkaz:
http://arxiv.org/abs/2307.11719
Knowledge graphs represent real-world entities and their relations in a semantically-rich structure supported by ontologies. Exploring this data with machine learning methods often relies on knowledge graph embeddings, which produce latent representa
Externí odkaz:
http://arxiv.org/abs/2306.12687
Ontology-based approaches for predicting gene-disease associations include the more classical semantic similarity methods and more recently knowledge graph embeddings. While semantic similarity is typically restricted to hierarchical relations within
Externí odkaz:
http://arxiv.org/abs/2105.04944
Publikováno v:
In Computers in Biology and Medicine March 2024 170
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Ontology Matching aims to find a set of semantic correspondences, called an alignment, between related ontologies. In recent years, there has been a growing interest in efficient and effective matching methods for large ontologies. However, most of t
Externí odkaz:
http://arxiv.org/abs/1307.5322
Autor:
Faria, Daniel, Pesquita, Catia, Santos, Emanuel, Couto, Francisco M., Stroe, Cosmin, Cruz, Isabel F.
The AgreementMaker system was the leading system in the anatomy task of the Ontology Alignment Evaluation Initiative (OAEI) competition in 2011. While AgreementMaker did not compete in OAEI 2012, here we report on its performance in the 2012 anatomy
Externí odkaz:
http://arxiv.org/abs/1212.1625