Zobrazeno 1 - 10
of 3 036
pro vyhledávání: '"heterogeneous information"'
Publikováno v:
International Journal of Web Information Systems, 2024, Vol. 20, Issue 6, pp. 603-620.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJWIS-04-2024-0116
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 2924-2933 (2024)
Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are closely related to the treatment of human diseases. Traditional biological experiments often require time-consuming and labor-intensive in their search for mechanisms of disease. Computational
Externí odkaz:
https://doaj.org/article/f696c5945aef451b8742c9eb81fa1cf0
Publikováno v:
Big Data Mining and Analytics, Vol 7, Iss 3, Pp 730-752 (2024)
Due to the heterogeneity of nodes and edges, heterogeneous network embedding is a very challenging task to embed highly coupled networks into a set of low-dimensional vectors. Existing models either only learn embedding vectors for nodes or only for
Externí odkaz:
https://doaj.org/article/dd5e750538b646d9b3fd035fccb498b7
Publikováno v:
Dianxin kexue, Vol 40, Pp 78-93 (2024)
Existing methods for heterogeneous network representation learning mainly focus on static networks, overlooking the significant impact of temporal attributes on node representations. However, real heterogeneous information networks are very dynamic,
Externí odkaz:
https://doaj.org/article/a080d51be7a445b087999aaedef22ed4
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 6, Pp 8163-8177 (2024)
Abstract With the continuous accumulation of massive amounts of mobile data, point-of-interest (POI) recommendation has become a vital task for location-based social networks. Deep neural networks or matrix factorization (MF) alone are challenging to
Externí odkaz:
https://doaj.org/article/6abf081c45bb478598ca663d785070a7
Autor:
Denis A. Sidorenko, Anatoly A. Shalyto
Publikováno v:
Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki, Vol 24, Iss 4, Pp 594-601 (2024)
The research presents the development of a heterogeneous graph neural network model for predicting gene-disease using existing genomic and medical data. The novelty of the approach is in integrating the principles of graph neural networks and heterog
Externí odkaz:
https://doaj.org/article/1114c058cce74923a1aac023b96842b9
Publikováno v:
Applied Network Science, Vol 9, Iss 1, Pp 1-28 (2024)
Abstract With real-world network systems typically comprising a large number of interactive components and inherently dynamic, Graph Continual Learning (GCL) has gained increasing popularity in recent years. Furthermore, most applications involve mul
Externí odkaz:
https://doaj.org/article/57a420f47f304f469ba4796920ebfb3b
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Abundant researches have consistently illustrated the crucial role of microRNAs (miRNAs) in a wide array of essential biological processes. Furthermore, miRNAs have been validated as promising therapeutic targets for addressing complex disea
Externí odkaz:
https://doaj.org/article/cd8d92a59c504719884b85212dbb9234
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 5, Pp 1232-1242 (2024)
As effective tools for dealing with uncertainty, three-way decision models have been widely applied in the study of conflict analysis. However, existing three-way conflict analysis models are mostly based on single-type conflict information systems,
Externí odkaz:
https://doaj.org/article/bfac53a763b6490f9ab831ce1cf8357e
Autor:
Burak Gulbay, Mehmet Demirci
Publikováno v:
Engineering Science and Technology, an International Journal, Vol 57, Iss , Pp 101791- (2024)
Addressing the expanding Advanced Persistent Threat (APT) landscape is crucial for governments, enterprises and threat intelligence research groups. While defenders often rely on tabular formats for assets like logs, alerts, firewall rules; attackers
Externí odkaz:
https://doaj.org/article/9c0698d76e5a458697626b1b27a6a295