Results 1 to 10 of about 31,208 (278)
Effective attributed network embedding with information behavior extraction [PDF]
PeerJ Computer Science, 2022 Network embedding has shown its effectiveness in many tasks, such as link prediction, node classification, and community detection. Most attributed network embedding methods consider topological features and attribute features to obtain a node embedding ...
Ganglin Hu, Jun Pang, Xian Mo
doaj +6 more sources
Attributed Social Network Embedding [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2018 12 pages, 7 ...
Tat-Seng Chua +2 more
exaly +7 more sources
Protein complexes identification based on go attributed network embedding [PDF]
BMC Bioinformatics, 2018 Background Identifying protein complexes from protein-protein interaction (PPI) network is one of the most important tasks in proteomics. Existing computational methods try to incorporate a variety of biological evidences to enhance the quality of ...
Bo Xu +6 more
doaj +4 more sources
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 ...
Chengqi Zhang, Daokun Zhang, Jie Yin
exaly +6 more sources
DANE-MDA: Predicting microRNA-disease associations via deep attributed network embedding [PDF]
iScience, 2021 Summary: Predicting the microRNA-disease associations by using computational methods is conductive to the efficiency of costly and laborious traditional bio-experiments.
Bo-Ya Ji +4 more
doaj +2 more sources
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 +3 more sources
Attributed network embedding based on self-attention mechanism for recommendation method [PDF]
Scientific Reports, 2023 Network embedding is a technique used to learn a low-dimensional vector representation for each node in a network. This method has been proven effective in network mining tasks, especially in the area of recommendation systems.
Shuo Wang, Jing Yang, Fanshu Shang
doaj +2 more sources
Structural Adversarial Variational Auto-Encoder for Attributed Network Embedding [PDF]
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 +2 more sources
Outlier Aware Network Embedding for Attributed Networks [PDF]
Proceedings of the AAAI Conference on Artificial Intelligence, 2019 Attributed network embedding has received much interest from the research community as most of the networks come with some content in each node, which is also known as node attributes. Existing attributed network approaches work well when the network is consistent in structure and attributes, and nodes behave as expected.
Sambaran Bandyopadhyay +2 more
openaire +4 more sources
HEAT: Hyperbolic Embedding of Attributed Networks [PDF]
, 2020 15 pages, 4 ...
David W. McDonald, Shan He 0001
openaire +5 more sources