Zobrazeno 1 - 10
of 251
pro vyhledávání: '"knowledge graph embeddings"'
Publikováno v:
Journal of Biomedical Semantics, Vol 14, Iss 1, Pp 1-12 (2023)
Abstract Background Predicting gene-disease associations typically requires exploring diverse sources of information as well as sophisticated computational approaches. Knowledge graph embeddings can help tackle these challenges by creating representa
Externí odkaz:
https://doaj.org/article/6ada3d712c204b728f17609745aafd3d
Publikováno v:
Transactions on Graph Data and Knowledge, Vol 1, Iss 1, Pp 8:1-8:35 (2023)
The graph model is nowadays largely adopted to model a wide range of knowledge and data, spanning from social networks to knowledge graphs (KGs), representing a successful paradigm of how symbolic and transparent AI can scale on the World Wide Web. H
Externí odkaz:
https://doaj.org/article/e696bd6a9ef64d9e89232b45b4077f3c
Autor:
Diego Rincon-Yanez, Chahinez Ounoughi, Bassem Sellami, Tarmo Kalvet, Marek Tiits, Sabrina Senatore, Sadok Ben Yahia
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 35, Iss 10, Pp 101789- (2023)
Knowledge representation (KR) is vital in designing symbolic notations to represent real-world facts and facilitate automated decision-making tasks. Knowledge graphs (KGs) have emerged so far as a popular form of KR, offering a contextual and human-l
Externí odkaz:
https://doaj.org/article/c4eb64dab0fc4c8d912cf0b7bac82ae7
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-17 (2023)
Abstract Background Intensive Care Unit (ICU) readmissions represent both a health risk for patients,with increased mortality rates and overall health deterioration, and a financial burden for healthcare facilities. As healthcare became more data-dri
Externí odkaz:
https://doaj.org/article/576a44d4886e431a871f91d95eaacbb9
Publikováno v:
Future Internet, Vol 16, Iss 1, p 12 (2023)
Educational content recommendation is a cornerstone of AI-enhanced learning. In particular, to facilitate navigating the diverse learning resources available on learning platforms, methods are needed for automatically linking learning materials, e.g.
Externí odkaz:
https://doaj.org/article/59d6b01a55b2403aa4e1f3f545bdbe6e
Publikováno v:
BMC Bioinformatics, Vol 23, Iss 1, Pp 1-19 (2022)
Abstract Background Drug repurposing aims at finding new targets for already developed drugs. It becomes more relevant as the cost of discovering new drugs steadily increases. To find new potential targets for a drug, an abundance of methods and exis
Externí odkaz:
https://doaj.org/article/bc47291f086341fd8c36f1644c2cdecd
Publikováno v:
Entropy, Vol 25, Iss 10, p 1472 (2023)
Link prediction remains paramount in knowledge graph embedding (KGE), aiming to discern obscured or non-manifest relationships within a given knowledge graph (KG). Despite the critical nature of this endeavor, contemporary methodologies grapple with
Externí odkaz:
https://doaj.org/article/ac313980e27247bcad1df17618218403
Autor:
Mirza Mohtashim Alam, Md Rashad Al Hasan Rony, Mojtaba Nayyeri, Karishma Mohiuddin, M. S. T. Mahfuja Akter, Sahar Vahdati, Jens Lehmann
Publikováno v:
IEEE Access, Vol 10, Pp 76008-76020 (2022)
Knowledge graph embedding models have become a popular approach for knowledge graph completion through predicting the plausibility of (potential) triples. This is performed by transforming the entities and relations of the knowledge graph into an emb
Externí odkaz:
https://doaj.org/article/b059c825278f45f99207ea8f7e1a7597
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