Zobrazeno 1 - 10
of 12 484
pro vyhledávání: '"Named Entity Recognition"'
Publikováno v:
Journal of Donghua University (English Edition); Oct2024, Vol. 41 Issue 5, p513-524, 12p
BioKGrapher: Initial evaluation of automated knowledge graph construction from biomedical literature
Autor:
Henning Schäfer, Ahmad Idrissi-Yaghir, Kamyar Arzideh, Hendrik Damm, Tabea M.G. Pakull, Cynthia S. Schmidt, Mikel Bahn, Georg Lodde, Elisabeth Livingstone, Dirk Schadendorf, Felix Nensa, Peter A. Horn, Christoph M. Friedrich
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 24, Iss , Pp 639-660 (2024)
Background The growth of biomedical literature presents challenges in extracting and structuring knowledge. Knowledge Graphs (KGs) offer a solution by representing relationships between biomedical entities. However, manual construction of KGs is labo
Externí odkaz:
https://doaj.org/article/bb5ff474e9dc4345913fc469fb7b07e5
Publikováno v:
Proceedings on Engineering Sciences, Vol 6, Iss 4, Pp 1757-1764 (2024)
Technological advancements have caused widespread shifts in the medical industry. A vast quantity of information may be found in the medical literature publications released by researchers. Natural language processing innovations have made it simple
Externí odkaz:
https://doaj.org/article/0c15a3e1c7704eee9662d199c4030817
Autor:
Hui Zhao, Wenjun Xiong
Publikováno v:
Alexandria Engineering Journal, Vol 107, Iss , Pp 665-674 (2024)
Named Entity Recognition (NER) in Chinese Electronic Medical Records (EMRs) is crucial for enhancing healthcare quality and efficiency. However, the unique complexity of the Chinese language and the unstructured format of medical texts create signifi
Externí odkaz:
https://doaj.org/article/a91602c5a23b47fb863cd4108b091e82
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Social media data are characterized by significant noise and non-standardization, thereby posing challenges for existing methods in recognizing named entities owing to the entity sparsity and insufficient semantic richness. Thus, to deal wit
Externí odkaz:
https://doaj.org/article/f51329f6adcd495abf9561a307ca4a7d
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 11, Pp 2901-2911 (2024)
In order to efficiently construct a multimodal subject knowledge graph in the field of education, a textbook text entity relationship extraction algorithm based on large model knowledge distillation and multi-model collaborative reasoning is proposed
Externí odkaz:
https://doaj.org/article/609afd248aa24a4c947802e66d13d396
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 10, Pp 2594-2615 (2024)
Named entity recognition aims to identify named entities and their types from unstructured text, which is an important basic task in natural language processing technologies such as question answering system, machine translation and knowledge graph.
Externí odkaz:
https://doaj.org/article/dcd60d5fd19742ce904b16caa2031d09
Autor:
Zhou, Huiwei1 (AUTHOR) zhouhuiwei@dlut.edu.cn, Liu, Zhe1 (AUTHOR), Lang, Chengkun1 (AUTHOR), Xu, Yibin1 (AUTHOR), Lin, Yingyu2 (AUTHOR), Hou, Junjie3 (AUTHOR)
Publikováno v:
BMC Bioinformatics. 6/2/2021 Supplement 6, Vol. 22 Issue 6, p1-16. 16p.
Autor:
Ali, Dilawar, Milleville, Kenzo, Verstockt, Steven, Van de Weghe, Nico, Chambers, Sally, Birkholz, Julie M.
Publikováno v:
Journal of Documentation, 2023, Vol. 80, Issue 5, pp. 1031-1056.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JD-01-2022-0029