Results 11 to 20 of about 30,518 (252)
Attributed network embedding via subspace discovery [PDF]
Data Mining and Knowledge Discovery, 2019 Network embedding aims to learn a latent, low-dimensional vector representations of network nodes, effective in supporting various network analytic tasks. While prior arts on network embedding focus primarily on preserving network topology structure to learn node representations, recently proposed attributed network embedding algorithms attempt to ...
Daokun Zhang, Jie Yin, Xingquan Zhu
exaly +4 more sources
Anchor Link Prediction across Attributed Networks via Network Embedding
Entropy, 2019 Presently, many users are involved in multiple social networks. Identifying the same user in different networks, also known as anchor link prediction, becomes an important problem, which can serve numerous applications, e.g., cross-network recommendation,
Shaokai Wang +6 more
doaj +3 more sources
Method of Attributed Heterogeneous Network Embedding with Multiple Features [PDF]
Jisuanji kexue, 2022 Network embedding aims to represent nodes in unstructured network with low-dimensional,real-valued vectors,so that node embedding can retain the structural and attribute features of the original network as much as possible.However,current research mainly
TANG Qi-you, ZHANG Feng-li, WANG Rui-jin, WANG Xue-ting, ZHOU Zhi-yuan, HAN Ying-jun
doaj +1 more source
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
doaj +1 more source
Attributed Network Embedding Based on Matrix Factorization and Community Detection [PDF]
Jisuanji kexue, 2021 An attributed network contains not only the complex topological structure but also the nodes with rich attribute information.It can be used to more effectively model modern information systems than traditional networks.Community detection of the ...
XU Xin-li, XIAO Yun-yue, LONG Hai-xia, YANG Xu-hua, MAO Jian-fei
doaj +1 more source
Network Embedding Algorithm Taking in Variational Graph AutoEncoder
Mathematics, 2022 Complex networks with node attribute information are employed to represent complex relationships between objects. Research of attributed network embedding fuses the topology and the node attribute information of the attributed network in the common ...
Dongming Chen +4 more
doaj +1 more source
Node Embedding Method Based on Folded Path Aggregation on Attributed Network [PDF]
Jisuanji gongcheng, 2023 Attributed network embedding is a challenging task in the field of graph analysis.It aims to learn the low-dimensional vector representation of nodes from the network topology and node attributes of the network while maintaining its structure and ...
Mingchang BAI
doaj +1 more source
Binarized attributed network embedding [PDF]
2018 IEEE International Conference on Data Mining (ICDM), 2018 Attributed network embedding enables joint representation learning of node links and attributes. Existing attributed network embedding models are designed in continuous Euclidean spaces which often introduce data redundancy and impose challenges to storage and computation costs.
Hong Yang 0003 +5 more
openaire +1 more source
Co-Embedding Attributed Networks [PDF]
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019 Existing embedding methods for attributed networks aim at learning low-dimensional vector representations for nodes only but not for both nodes and attributes, resulting in the fact that they cannot capture the affinities between nodes and attributes. However, capturing such affinities is of great importance to the success of many real-world attributed
Zaiqiao Meng +3 more
openaire +1 more source
Structural Adversarial Variational Auto-Encoder for Attributed Network Embedding
Applied Sciences, 2021 As most networks come with some content in each node, attributed network embedding has aroused much research interest. Most existing attributed network embedding methods aim at learning a fixed representation for each node encoding its local proximity ...
Junjian Zhan +4 more
doaj +1 more source