Zobrazeno 1 - 10
of 186
pro vyhledávání: '"Heterogeneous graphs"'
MVD-HG: multigranularity smart contract vulnerability detection method based on heterogeneous graphs
Publikováno v:
Cybersecurity, Vol 7, Iss 1, Pp 1-15 (2024)
Abstract Smart contracts have significant losses due to various types of vulnerabilities. However, traditional vulnerability detection methods rely extensively on expert rules, resulting in low detection accuracy and poor adaptability to novel attack
Externí odkaz:
https://doaj.org/article/b5efcd0eeddb4fe09c9afbf409f90ea0
Publikováno v:
Data Science and Engineering, Vol 9, Iss 3, Pp 294-308 (2024)
Abstract Recently, with graph neural networks (GNNs) becoming a powerful technique for graph representation, many excellent GNN-based models have been proposed for processing heterogeneous graphs, which are termed Heterogeneous graph neural networks
Externí odkaz:
https://doaj.org/article/f8df599866344b7583095f0bde0c7285
Publikováno v:
Data Science and Engineering, Vol 9, Iss 2, Pp 220-237 (2024)
Abstract Community search (CS) is a vital research area in network science that focuses on discovering personalized communities for query vertices from graphs. However, existing CS methods mainly concentrate on homogeneous or simple attributed graphs
Externí odkaz:
https://doaj.org/article/11131ec2a3c341788512d52a39674e09
Autor:
Marcos Paulo Silva Gôlo, Marcelo Isaias de Moraes Junior, Rudinei Goularte, Ricardo Marcondes Marcacini
Publikováno v:
Journal on Interactive Systems, Vol 15, Iss 1 (2024)
Heterogeneous graphs are an essential structure that models real-world data through different types of nodes and relationships between them, including multimodality, which comprises different types of data such as text, image, and audio. Graph Neural
Externí odkaz:
https://doaj.org/article/8613d55723914e3e91c466c5a1de7169
Publikováno v:
BMC Genomics, Vol 24, Iss 1, Pp 1-14 (2023)
Abstract Increasing evidence has shown that the expression of circular RNAs (circRNAs) can affect the drug sensitivity of cells and significantly influence drug efficacy. Therefore, research into the relationships between circRNAs and drugs can be of
Externí odkaz:
https://doaj.org/article/5ba3452c6cce4dbd8b752a99b1b12c07
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 11, Pp 20050-20072 (2023)
The primary objective of document-level event extraction is to extract relevant event information from lengthy texts. However, many existing methods for document-level event extraction fail to fully incorporate the contextual information that spans a
Externí odkaz:
https://doaj.org/article/642933a393764e348e9b89e6b8738828
Autor:
Longhai Li, Lei Duan, Junchen Wang, Chengxin He, Zihao Chen, Guicai Xie, Song Deng, Zhaohang Luo
Publikováno v:
Data Science and Engineering, Vol 8, Iss 2, Pp 98-111 (2023)
Abstract Temporal heterogeneous graphs can model lots of complex systems in the real world, such as social networks and e-commerce applications, which are naturally time-varying and heterogeneous. As most existing graph representation learning method
Externí odkaz:
https://doaj.org/article/9c2dd132f1764c78b95fe4c4f6ba72e5
Publikováno v:
IEEE Access, Vol 11, Pp 27609-27619 (2023)
This paper introduces a novel method that integrates structural information with training deep neural models to solve math word problems. Prior works adopt the graph structure to represent rich information residing in the input sentences. However, th
Externí odkaz:
https://doaj.org/article/656cf105fc9a4f399534735714dd2315
Publikováno v:
Frontiers in Pharmacology, Vol 14 (2023)
Background: Inferring drug-related side effects is beneficial for reducing drug development cost and time. Current computational prediction methods have concentrated on graph reasoning over heterogeneous graphs comprising the drug and side effect nod
Externí odkaz:
https://doaj.org/article/f314529ae8b54209b8807b6de17cc72b
Publikováno v:
Applied Sciences, Vol 14, Iss 4, p 1601 (2024)
Business intelligence (BI), as a system for business data integration, processing, and analysis, is receiving increasing attention from enterprises. Data visualization is an important feature of BI, which allows users to visually observe the distribu
Externí odkaz:
https://doaj.org/article/3cc086ce4ed844498d153d0ee122f4fb