Results 21 to 30 of about 4,728,201 (299)
Hierarchical Labels Guided Attributed Network Embedding
Jisuanji kexue yu tansuo, 2021 Network embedding, aiming to learn low dimensional vectors for nodes while preserving important properties of the network, benefits plenty of network applications.
CHEN Jie, CHEN Jialin, ZHAO Shu, ZHANG Yanping
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MERP: Motifs enhanced network embedding based on edge reweighting preprocessing
Frontiers in Physics, 2022 Network embedding has attracted a lot of attention in different fields recently. It represents nodes in a network into a low-dimensional and dense space while preserving the structural properties of the network. Some methods (e.g.
Shaoqing Lv +4 more
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MFHE: Multi-View Fusion-Based Heterogeneous Information Network Embedding
Applied Sciences, 2022 Depending on the type of information network, information network embedding is classified into homogeneous information network embedding and heterogeneous information network (HIN) embedding. Compared with the homogeneous network, HIN composition is more
Tingting Liu, Jian Yin, Qingfeng Qin
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GCMD: Genetic Correlation Multi-Domain Virtual Network Embedding Algorithm
IEEE Access, 2021 With the increase of network scale and the complexity of network structure, the problems of traditional Internet have emerged. At the same time, the appearance of network function virtualization (NFV) and network virtualization technologies has largely ...
Peiying Zhang +5 more
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Reinforcement learning-based virtual network embedding: A comprehensive survey
ICT Express, 2023 Virtual network embedding plays a vital role in network virtualization, as it determines the deployment and connection of virtual networks to the physical network in the 5G and beyond.
Hyun-Kyo Lim +3 more
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Deep Attributed Network Embedding via Weisfeiler-Lehman and Autoencoder
IEEE Access, 2022 Network embedding plays a critical role in many applications. Node classification, link prediction, and network visualization are examples of such applications.
Amr Thabit Al-Furas +3 more
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Context Embedding Networks [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Low dimensional embeddings that capture the main variations of interest in collections of data are important for many applications. One way to construct these embeddings is to acquire estimates of similarity from the crowd. However, similarity is a multi-dimensional concept that varies from individual to individual.
Kim, Kun Ho +2 more
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Network-based embedding methods for multi-omics data analysis [PDF]
, 2023 The development of high-throughput technologies has resulted in a significant increase in data, opening up new opportunities to study and better understand how biological systems dynamically interact. Network analysis, which is based on graph theory, can
Parvizi, Poorya
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Network representation learning systematic review: Ancestors and current development state
Machine Learning with Applications, 2021 Real-world information networks are increasingly occurring across various disciplines including online social networks and citation networks. These network data are generally characterized by sparseness, nonlinearity and heterogeneity bringing different ...
Amina Amara +2 more
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Embedding-aided network dismantling
Physical Review Research, 2023 Optimal percolation concerns the identification of the minimum-cost strategy for the destruction of any extensive connected components in a network. Solutions of such a dismantling problem are important for the design of optimal strategies of disease ...
Saeed Osat +3 more
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