Referenced Items are not available for this document.
The size and interconnectedness of social networks continues to increase. As a result, finding communities or subsets of like nodes within these large networks has become a resource-intensive endeavor. In this paper, we characterize community-finding organized on the basis of network/set properties, and describe an agglomerative algorithm called egocentric community finding. The primary contribution of this paper is a performance evaluation in which the egocentric data-mining algorithm is optimized for execution on various computing platforms, including GPU's, multicore systems, and large-scale distributed systems.
Published in:
Electro/Information Technology (EIT), 2012 IEEE International Conference on
Date of Conference: 6-8 May 2012
- Page(s):
- 1 - 6
- ISSN :
- 2154-0357
- Print ISBN:
- 978-1-4673-0819-9
- INSPEC Accession Number:
- 12821456
- Conference Location :
- Indianapolis, IN
- Digital Object Identifier :
- 10.1109/EIT.2012.6220744
- Product Type:
- Conference Publications
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