Using graph-based metrics with empirical risk minimization to speed up active learning on networked data

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Author:

Sofus A. Macskassy

Fetch Technologies, El Segundo, CA, USA

Published in:

	· Proceeding
	KDD '09 Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
	Pages 597-606 ACM New York, NY, USA ©2009 table of contents ISBN: 978-1-60558-495-9 doi>10.1145/1557019.1557087

	2009 Article
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Tags: active learning algorithms betweenness centrality closeness centrality clustering community finding concept learning design empirical risk minimization experimentation graph algorithms graphs and networks performance semi-supervised learning social network analysis statistical relational learning within-network learning