Literatura científica selecionada sobre o tema "Uration continue des KGs"
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Artigos de revistas sobre o assunto "Uration continue des KGs"
Yuan, Jun, Neng Gao e Ji Xiang. "TransGate: Knowledge Graph Embedding with Shared Gate Structure". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julho de 2019): 3100–3107. http://dx.doi.org/10.1609/aaai.v33i01.33013100.
Texto completo da fonteIqbal, Javaid, Sunil Dutt Sharma, Ashu Jamwal e Ghanshyam Saini. "Acute bilirubin encephalopathy in term neonates: a hospital-based study". International Journal of Research in Medical Sciences 7, n.º 4 (27 de março de 2019): 1109. http://dx.doi.org/10.18203/2320-6012.ijrms20191308.
Texto completo da fonteFrutos, Cristobal A., Barbara Konkle, Jorge Batista, Silvia Brizuela, Elvira Enciso, Gustavo Fernandez, Adolfo Gaona, Helga Martinez, Alma M. Poisson e Marlene Rivarola. "Prophylaxis in Patients with Hemophilia a and Its Impact on Quality of Life Using the Specific Index Haem-a-Qol at a Hospital in Paraguay". Blood 128, n.º 22 (2 de dezembro de 2016): 4959. http://dx.doi.org/10.1182/blood.v128.22.4959.4959.
Texto completo da fonteZehra, Ambreen, e Sarwar Jahan Abbas. "Hybrid Learning and Teaching in Mathematics Courses Due to COVID-19". Punjab University Journal of Mathematics, 31 de agosto de 2022, 535–42. http://dx.doi.org/10.52280/pujm.2022.540803.
Texto completo da fonteSarmalkar, Meenal, Abhakumari Abhakumari e Madhuri Mehendale. "“STUDY OF PRETERM DELIVERY AT TERTIARY CARE HOSPITAL”". INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH, 1 de agosto de 2022, 80–82. http://dx.doi.org/10.36106/ijsr/3905678.
Texto completo da fonteTeses / dissertações sobre o assunto "Uration continue des KGs"
Ahmadi, Naser. "A framework for the continuous curation of a knowledge base system". Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS320.
Texto completo da fonteEntity-centric knowledge graphs (KGs) are becoming increasingly popular for gathering information about entities. The schemas of KGs are semantically rich, with many different types and predicates to define the entities and their relationships. These KGs contain knowledge that requires understanding of the KG’s structure and patterns to be exploited. Their rich data structure can express entities with semantic types and relationships, oftentimes domain-specific, that must be made explicit and understood to get the most out of the data. Although different applications can benefit from such rich structure, this comes at a price. A significant challenge with KGs is the quality of their data. Without high-quality data, the applications cannot use the KG. However, as a result of the automatic creation and update of KGs, there are a lot of noisy and inconsistent data in them and, because of the large number of triples in a KG, manual validation is impossible. In this thesis, we present different tools that can be utilized in the process of continuous creation and curation of KGs. We first present an approach designed to create a KG in the accounting field by matching entities. We then introduce methods for the continuous curation of KGs. We present an algorithm for conditional rule mining and apply it on large graphs. Next, we describe RuleHub, an extensible corpus of rules for public KGs which provides functionalities for the archival and the retrieval of rules. We also report methods for using logical rules in two different applications: teaching soft rules to pre-trained language models (RuleBert) and explainable fact checking (ExpClaim)