Results 231 to 240 of about 6,752,678 (299)

Knowledge graph embeddings in the biomedical domain: are they useful? A look at link prediction, rule learning, and downstream polypharmacy tasks. [PDF]

Bioinform Adv
Gema AP, Grabarczyk D, De Wulf W, Borole P, Alfaro JA, Minervini P, Vergari A, Rajan A.   +7 more
europepmc   +1 more source

Dynamic network link prediction with node representation learning from graph convolutional networks. [PDF]

Sci Rep
Mei P, Zhao YH.
europepmc   +1 more source

The effectiveness of intervention measures on MERS-CoV transmission by using the contact networks reconstructed from link prediction data. [PDF]

Front Public Health
Kim E, Kim Y, Jin H, Lee Y, Lee H, Lee S.   +5 more
europepmc   +1 more source

GraphSage for Link Prediction

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Interpretable link prediction

Chaos, Solitons & Fractals
Hailun Tan, Yan Liu, Xinying Liu, Lianyu Hu, Zengyou He   +4 more
semanticscholar   +2 more sources

A Multi-Type Transferable Method for Missing Link Prediction in Heterogeneous Social Networks

IEEE Transactions on Knowledge and Data Engineering, 2023
Heterogeneous social networks, which are characterized by diverse interaction types, have resulted in new challenges for missing link prediction. Most deep learning models tend to capture type-specific features to maximize the prediction performances on ...
Huan Wang, Ziwen Cui, Ruigang Liu, Lei Fang, Ying Sha   +4 more
semanticscholar   +1 more source

HyConvE: A Novel Embedding Model for Knowledge Hypergraph Link Prediction with Convolutional Neural Networks

The Web Conference, 2023
Knowledge hypergraph embedding, which projects entities and n-ary relations into a low-dimensional continuous vector space to predict missing links, remains a challenging area to be explored despite the ubiquity of n-ary relational facts in the real ...
Chenxu Wang, Xin Wang, Zhao Li, Zi-Yuan Chen, Jianxin Li   +4 more
semanticscholar   +1 more source

Link prediction

Proceedings of the 20th ACM international conference on Information and knowledge management, 2011
Link prediction is a fundamental problem in social network analysis. The key technique in unsupervised link prediction is to find an appropriate similarity measure between nodes of a network. A class of wildly used similarity measures are based on random walk on graph.
Rong-Hua Li, Jeffrey Xu Yu, Jianquan Liu
openaire   +2 more sources

Euler: Detecting Network Lateral Movement via Scalable Temporal Link Prediction

ACM Transactions on Privacy and Security, 2023
Lateral movement is a key stage of system compromise used by advanced persistent threats. Detecting it is no simple task. When network host logs are abstracted into discrete temporal graphs, the problem can be reframed as anomalous edge detection in an ...
I. J. King, Huimin Huang
semanticscholar   +1 more source