A Joint Community Detection Model: Integrating Directed and Undirected Probabilistic Graphical Models via Factor Graph With Attention Mechanism

He, Dongxiao; Liu, Huixin; Feng, Zhiyong; Wang, Xiaobao; Jin, Di; Song, Wenze; Huang, Yuxiao

doi:10.1109/tbdata.2021.3104005

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

A Joint Community Detection Model: Integrating Directed and Undirected Probabilistic Graphical Models via Factor Graph With Attention Mechanism

Cited by 3 publications

References 46 publications

Detecting communities with multiple topics in attributed networks via self-supervised adaptive graph convolutional network

Detecting communities with multiple topics in attributed networks via self-supervised adaptive graph convolutional network

Community Detection with Graph Convolutional Auto-Encoder and Deep Clustering

Multiple Topics Community Detection in Attributed Networks

Contact Info

Product

Resources

About