Zobrazeno 1 - 10
of 221
pro vyhledávání: '"Sun, Yifang"'
Publikováno v:
In Acta Psychologica October 2024 250
Autor:
Sun, Yifang1 (AUTHOR), Wu, Jian2 (AUTHOR), Zhang, Qian2 (AUTHOR), Wang, Pengzhen3 (AUTHOR), Zhang, Jinglin4 (AUTHOR) zhjinglin@126.com, Yuan, Yonggang1 (AUTHOR) ophthalmology2022@163.com
Publikováno v:
Journal of Translational Medicine. 7/29/2024, Vol. 22 Issue 1, p1-16. 16p.
Autor:
Du, Jiazong, Hu, Limin, Yao, Zhengquan, Liu, Xiting, Sun, Yifang, Yang, Gang, Aksentov, Kirill, Vasilenko, Yuriy, Bosin, Alexander, Astakhov, Anatolii, Shi, Xuefa
Publikováno v:
In Chemical Geology 20 December 2024 670
The rapid growth in published clinical trials makes it difficult to maintain up-to-date systematic reviews, which requires finding all relevant trials. This leads to policy and practice decisions based on out-of-date, incomplete, and biased subsets o
Externí odkaz:
http://arxiv.org/abs/2109.02254
Fine-Grained Named Entity Typing (FG-NET) aims at classifying the entity mentions into a wide range of entity types (usually hundreds) depending upon the context. While distant supervision is the most common way to acquire supervised training data, i
Externí odkaz:
http://arxiv.org/abs/2101.11212
Fine-Grained Named Entity Typing (FG-NET) is a key component in Natural Language Processing (NLP). It aims at classifying an entity mention into a wide range of entity types. Due to a large number of entity types, distant supervision is used to colle
Externí odkaz:
http://arxiv.org/abs/2004.03554
Due to the outstanding capability of capturing underlying data distributions, deep learning techniques have been recently utilized for a series of traditional database problems. In this paper, we investigate the possibilities of utilizing deep learni
Externí odkaz:
http://arxiv.org/abs/2002.06442
To tackle Named Entity Recognition (NER) tasks, supervised methods need to obtain sufficient cleanly annotated data, which is labor and time consuming. On the contrary, distantly supervised methods acquire automatically annotated data using dictionar
Externí odkaz:
http://arxiv.org/abs/1912.01731
Akademický článek
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Autor:
Zhang, Huidan, Lv, Ying, Chang, Yulei, Guo, Xiaoyang, Zou, Deyue, Sun, Yifang, Zeng, Qinghui, Liu, Xingyuan
Publikováno v:
In Chemical Engineering Journal 1 October 2023 473