preprintJan 1, 2013Closed access
4 Community Detection in Networks with Node Attributes
JYJaewon YangJMJulian McauleyJLJure Leskovec
Abstract
Abstract—Community detection algorithms are fundamental tools that allow us to uncover organizational principles in networks. When detecting communities, there are two possible sources of information one can use: the network structure, and the features and attributes of nodes. Even though communities form around nodes that have common edges and common attributes, typically, algorithms have only focused on one of these two data modalities: community detection algorithms traditionally focus only on the network structure, while clustering algorithms mostly consider only node attributes. In this paper, we develop Com-munities from Edge Structure and Node Attributes (CESNA), an accurate and scalable algorithm for…
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Authors
3- JYJaewon YangCorresponding
- JMJulian Mcauley
- JLJure Leskovec
Topics & keywords
Topics
Keywords
- Computer science
- Community structure
- Robustness (evolution)
- Data mining
- Node (physics)
- Cluster analysis
- Focus (optics)
- Scalability
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