Zobrazeno 1 - 10
of 1 114
pro vyhledávání: '"machine reading"'
Publikováno v:
大数据, Vol 10, Pp 121-129 (2024)
In the era of informatization and digitization, the rapid increase in the number of scientific papers has given rise to various challenges, such as lengthy articles, difficulty in information extraction and high time costs associated with reading.Lit
Externí odkaz:
https://doaj.org/article/1b6ff7513b9a460fa707ba5dc9d06fe7
Autor:
Zihui Huang, Liqiang He, Yuhang Yang, Andi Li, Zhiwen Zhang, Siwei Wu, Yang Wang, Yan He, Xujie Liu
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-10 (2024)
Abstract Materials science is an interdisciplinary field that studies the properties, structures, and behaviors of different materials. A large amount of scientific literature contains rich knowledge in the field of materials science, but manually an
Externí odkaz:
https://doaj.org/article/39d66da1f66841ed9fc82acc8a585694
Publikováno v:
In Knowledge-Based Systems 30 January 2025 309
Autor:
Yuanyu Feng, Yan Zhou
Publikováno v:
IEEE Access, Vol 12, Pp 113235-113243 (2024)
Traditional Chinese medicine (TCM) named entity recognition for supporting downstream tasks is receiving increasing attention. However, mainstream named entity recognition models applied to the TCM domain are still affected by the following two chall
Externí odkaz:
https://doaj.org/article/e7b93dce9a94435c94f7fa27c043f266
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7794 (2024)
To address the problems of the insufficient semantic fusion between text and questions and the lack of consideration of global semantic information encountered in machine reading comprehension models, we proposed a machine reading comprehension model
Externí odkaz:
https://doaj.org/article/09affc79840241df9649a63413224ffc
Autor:
Duanduan Liu
Publikováno v:
Intelligent Systems with Applications, Vol 21, Iss , Pp 200307- (2024)
With the rapid development of machine learning, challenging question and answer datasets have also emerged, and the machine reading comprehension technology has emerged. Traditional machine reading comprehension methods mostly focus on the understand
Externí odkaz:
https://doaj.org/article/01edba10124542fbb7efa3d1925d0fb5
Publikováno v:
International Journal of Cognitive Computing in Engineering, Vol 4, Iss , Pp 118-126 (2023)
Judicial named entity recognition (JNER) is a basic task of judicial intelligence and judicial service informatization. At present, the research of JNER has attracted extensive attention. However, the existing JNER methods usually can only assign a s
Externí odkaz:
https://doaj.org/article/a2a46172c023441ba404239b57d819c6
Autor:
Liu Jie
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
With the trend of information technology, contemporary English language teaching is moving positively in the direction of intelligence. This study utilizes the text embedding model to represent language and convert it into a format that computers can
Externí odkaz:
https://doaj.org/article/7217921ed989442994a919525b76781e
Publikováno v:
Intelligent Systems with Applications, Vol 20, Iss , Pp 200287- (2023)
Deep neural networks, despite their remarkable success in various language understanding tasks, have been found vulnerable to adversarial attacks and subtle input perturbations, revealing a robustness shortfall. To explore this, this paper presents R
Externí odkaz:
https://doaj.org/article/ef7a1cde42f9499aadbbbcfa9f35b27c
Publikováno v:
Jisuanji kexue, Vol 50, Iss 2, Pp 275-284 (2023)
Event extraction aims to extract structured information automatically from massive unstructured texts to help people quickly understand the latest developments of events.Traditional methods are mainly implemented by classification or sequence labelin
Externí odkaz:
https://doaj.org/article/32a4f55b7b284c95b16bac1cc9486828