Centrality measures-based algorithm to visualize a maximal common induced subgraph in large communication networks

标题
Centrality measures-based algorithm to visualize a maximal common induced subgraph in large communication networks
作者
关键词
Communication networks, Similarity pattern, Graph mining, Substructure mining, Information extraction, Graph algorithm
出版物
KNOWLEDGE AND INFORMATION SYSTEMS
Volume 46, Issue 1, Pages 213-239
出版商
Springer Nature
发表日期
2015-05-29
DOI
10.1007/s10115-015-0844-5

向作者/读者发起求助以获取更多资源

Reprint

联系作者

Add your recorded webinar

Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.

Upload Now

Ask a Question. Answer a Question.

Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.

Get Started