Results 21 to 30 of about 30,518 (252)
Academic Collaborator Recommendation Based on Attributed Network Embedding
Journal of Data and Information Science, 2022 Based on real-world academic data, this study aims to use network embedding technology to mining academic relationships, and investigate the effectiveness of the proposed embedding model on academic collaborator recommendation tasks.
Du Ouxia, Li Ya
doaj +1 more source
Embedding Networks with Edge Attributes [PDF]
Proceedings of the 29th on Hypertext and Social Media, 2018 Predicting links in information networks requires deep understanding and careful modeling of network structure. Network embedding, which aims to learn low-dimensional representations of nodes, has been used successfully for the task of link prediction in the past few decades.
Palash Goyal +3 more
openaire +1 more source
Deep Attributed Network Embedding [PDF]
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Network embedding has attracted a surge of attention in recent years. It is to learn the low-dimensional representation for nodes in a network, which benefits downstream tasks such as node classification and link prediction. Most of the existing approaches learn node representations only based on the topological structure, yet nodes are often ...
Hongchang Gao, Heng Huang 0001
openaire +1 more source
Recommendation algorithm based on attributed multiplex heterogeneous network [PDF]
PeerJ Computer Science, 2021 In the field of deep learning, the processing of large network models on billions or even tens of billions of nodes and numerous edge types is still flawed, and the accuracy of recommendations is greatly compromised when large network embeddings are ...
Zhisheng Yang, Jinyong Cheng
doaj +2 more sources
Attributed Graph Embedding with Random Walk Regularization and Centrality-Based Attention
Mathematics, 2023 Graph-embedding learning is the foundation of complex information network analysis, aiming to represent nodes in a graph network as low-dimensional dense real-valued vectors for the application in practical analysis tasks.
Yuxuan Yang +4 more
doaj +1 more source
Inter-Intra Information Preserving Attributed Network Embedding
IEEE Access, 2019 To alleviate the problem caused by the sparsity of network structure which is often the case in large-scale network, attributed network embedding has attracted an increasing amount of attention. Some existing attributed network embedding models integrate
Kai Wang +5 more
doaj +1 more source
Unsupervised Attributed Multiplex Network Embedding
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Nodes in a multiplex network are connected by multiple types of relations. However, most existing network embedding methods assume that only a single type of relation exists between nodes. Even for those that consider the multiplexity of a network, they overlook node attributes, resort to node labels for training, and fail to model the global ...
Chanyoung Park 0001 +3 more
openaire +3 more sources
Flexible Attributed Network Embedding
CoRR, 2018 Network embedding aims to find a way to encode network by learning an embedding vector for each node in the network. The network often has property information which is highly informative with respect to the node's position and role in the network. Most network embedding methods fail to utilize this information during network representation learning ...
Enya Shen +3 more
openaire +2 more sources
Frontiers in Physics, 2022 Node classification, as a central task in the graph data analysis, has been studied extensively with network embedding technique for single-layer graph network. However, there are some obstacles when extending the single-layer network embedding technique
Beibei Han +4 more
doaj +1 more source
A Network Embedding-Enhanced NMF Method for Finding Communities in Attributed Networks
IEEE Access, 2022 Community detection is an extremely important task for complex network analysis. There still remains a challenge of how to improve the performance of community detection in real-world scenario.
Jinxin Cao +6 more
doaj +1 more source