Zobrazeno 1 - 10
of 724
pro vyhledávání: '"Graph attention networks"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Aspect-based sentiment analysis (ABSA) is a challenging task due to the presence of multiple aspect words with different sentiment polarities in a sentence. Recently, pre-trained language models like BERT have been widely used as context enc
Externí odkaz:
https://doaj.org/article/5d074dce7029422697431680bcd46843
Publikováno v:
Heliyon, Vol 10, Iss 16, Pp e35938- (2024)
In previous research, the prevailing assumption was that Graph Neural Networks (GNNs) precisely depicted the interconnections among nodes within the graph's architecture. Nonetheless, real-world graph datasets are often rife with noise, elements that
Externí odkaz:
https://doaj.org/article/b6d14e9dd9f5419b8dc59525a5e2be6a
Publikováno v:
Electronic Research Archive, Vol 32, Iss 4, Pp 2310-2322 (2024)
Graph convolution networks (GCN) have demonstrated success in learning graph structures; however, they are limited in inductive tasks. Graph attention networks (GAT) were proposed to address the limitations of GCN and have shown high performance in g
Externí odkaz:
https://doaj.org/article/5332fa983831429cbab5e0dff4d21a33
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-16 (2024)
Abstract Background In recent years, the extensive use of drugs and antibiotics has led to increasing microbial resistance. Therefore, it becomes crucial to explore deep connections between drugs and microbes. However, traditional biological experime
Externí odkaz:
https://doaj.org/article/133c0ab8619d40e8b88eaebcea780ded
Publikováno v:
Frontiers in Microbiology, Vol 15 (2024)
IntroductionAccumulating evidence shows that human health and disease are closely related to the microbes in the human body.MethodsIn this manuscript, a new computational model based on graph attention networks and sparse autoencoders, called GCANCAE
Externí odkaz:
https://doaj.org/article/9a9828a7feb240f9a18a21e0e0608281
Publikováno v:
PeerJ Computer Science, Vol 10, p e2200 (2024)
The rapid dissemination of unverified information through social platforms like Twitter poses considerable dangers to societal stability. Identifying real versus fake claims is challenging, and previous work on rumor detection methods often fails to
Externí odkaz:
https://doaj.org/article/754288c9bff74b6b870065462b53e927
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 5, Pp 102070- (2024)
Discovering trending social events (e.g., major meetings, political scandals, natural disasters, etc.) from social messages is vital because it emphasizes important events and can help people comprehend the world. However, the heterogeneous semantics
Externí odkaz:
https://doaj.org/article/517592c600144cd09bd8be7fd4afedea
Autor:
Md Easin Hasan, Amy Wagler
Publikováno v:
Healthcare Analytics, Vol 5, Iss , Pp 100310- (2024)
Neuronal cell segmentation identifies and separates individual neurons in an image, typically to study their properties or analyze their organization in the nervous system. This is significant because neurological problems and diseases can only be tr
Externí odkaz:
https://doaj.org/article/ea672b2b5230440d96eb3b8272a0e8ab
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
The precise fault localization holds significant importance in reducing power outage duration and frequency in power systems. The widespread application of synchrophasor measurement technology (PMU) has laid the foundation for achieving accurate faul
Externí odkaz:
https://doaj.org/article/cff7255b8f2f4a599d40606c939024e0
Autor:
Elena Tiukhova, Emiliano Penaloza, Maria Oskarsdottir, Bart Baesens, Monique Snoeck, Cristian Bravo
Publikováno v:
IEEE Access, Vol 12, Pp 115026-115041 (2024)
Leveraging network information for predictive modeling has become widespread in many domains. Within the realm of referral and targeted marketing, influencer detection stands out as an area that could greatly benefit from the incorporation of dynamic
Externí odkaz:
https://doaj.org/article/c996a016d3834582aec98711905b9e24