Zobrazeno 1 - 10
of 1 747
pro vyhledávání: '"Liu Peipei"'
Publikováno v:
Zhongguo quanke yixue, Vol 27, Iss 05, Pp 622-627 (2024)
Background With the accelerated aging of the national population, the rapid increase of the elderly with dementia has become an increasingly prominent problem. Sleep is the basic need of the human body, and sleep problems have become an independent r
Externí odkaz:
https://doaj.org/article/ed40c49c7ca84f40acc491abf4fe310f
Publikováno v:
Hangkong gongcheng jinzhan, Vol 12, Iss 2, Pp 21-29 (2021)
Predictive maintenance technique basing on real-time acquisition, transmission and analysis of aircraft data has been a trend in aviation industry.Starting from the technical connotation and systematic function of aircraft maintenance, combining with
Externí odkaz:
https://doaj.org/article/78295a22aaec486ca60f7363cd88e5de
Document-level relation extraction (DocRE) aims to extract relations between entities from unstructured document text. Compared to sentence-level relation extraction, it requires more complex semantic understanding from a broader text context. Curren
Externí odkaz:
http://arxiv.org/abs/2407.21384
Autor:
Yu Ling, Ye Mingxia, Zhang Xiaoyan, Fan Yifan, Liu Peipei, Zhang Yue, Meng Yuanguang, Li Lian
Publikováno v:
Frontiers in Surgery, Vol 8 (2021)
Background: The coronavirus disease 2019 (COVID-19) had become a health care event endangering humans globally. It takes up a large number of healthcare resources. We studied the impact of COVID-19 on patients with ovarian cancer by comprehensively a
Externí odkaz:
https://doaj.org/article/09820292e12943bdabb6e0782018233e
Few-shot named entity recognition can identify new types of named entities based on a few labeled examples. Previous methods employing token-level or span-level metric learning suffer from the computational burden and a large number of negative sampl
Externí odkaz:
http://arxiv.org/abs/2404.06970
Mining structured knowledge from tweets using named entity recognition (NER) can be beneficial for many down stream applications such as recommendation and intention understanding. With tweet posts tending to be multimodal, multimodal named entity re
Externí odkaz:
http://arxiv.org/abs/2305.08372
Modality representation learning is an important problem for multimodal sentiment analysis (MSA), since the highly distinguishable representations can contribute to improving the analysis effect. Previous works of MSA have usually focused on multimod
Externí odkaz:
http://arxiv.org/abs/2210.15824
Named Entity Recognition (NER) on social media refers to discovering and classifying entities from unstructured free-form content, and it plays an important role for various applications such as intention understanding and user recommendation. With s
Externí odkaz:
http://arxiv.org/abs/2210.14163
Enterprise relation extraction aims to detect pairs of enterprise entities and identify the business relations between them from unstructured or semi-structured text data, and it is crucial for several real-world applications such as risk analysis, r
Externí odkaz:
http://arxiv.org/abs/2210.10581