A common problem in modern graph analysis is the detection of communities, an example of which is the detection of a single anomalously dense subgraph. Recent results have demonstrated a fundamental limit for this problem when using spectral analysis of modularity. In this paper, we demonstrate the implication of these results on subgraph detection when a cue vertex is provided, indicating one of the vertices in the community of interest. Several recent algorithms for local community detection are applied in this context, and we compare their empirical performance to that of the simple method used to derive the theoretical detection limits.
|Title of host publication||Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015|
|Editors||Michael B. Matthews|
|Publisher||IEEE Computer Society|
|Number of pages||5|
|State||Published - 26 Feb 2016|
|Event||49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States|
Duration: 8 Nov 2015 → 11 Nov 2015
|Name||Conference Record - Asilomar Conference on Signals, Systems and Computers|
|Conference||49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015|
|Period||8/11/15 → 11/11/15|
Bibliographical notePublisher Copyright:
© 2015 IEEE.
ASJC Scopus subject areas
- Signal Processing
- Computer Networks and Communications