FLIP-CPM: A parallel community detection method

Computer and Information Sciences II - 26th International Symposium on Computer and Information Sciences, ISCIS 2011

Volumn , Issue , 2012, Pages 249-255

  Gregori, Enrico ^a   Lenzini, Luciano ^b   Mainardi, Simone ^a,b   Orsini, Chiara ^a,b  

^a CNR   (Italy)

^b UNIVERSITY OF PISA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CLIQUE PERCOLATION; COMMUNITY DETECTION; COMMUNITY STRUCTURES; COMPUTATIONAL LOADS; FUNCTIONAL ORGANIZATION; INNOVATIVE METHOD; MEMORY RESOURCES; SPEED-UP FACTORS;

PARALLEL ARCHITECTURES; SOLVENTS;

INFORMATION SCIENCE;

EID: 84887838387     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-1-4471-2155-8-31     Document Type: Conference Paper

References (7)

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2. Eppstein, D., Galil, Z., Italiano, G.F.: Dynamic graph algorithms.In: Atallah, M.J.(ed.) Algorithms and Theory of Computation Handbook.Purdue University, CRC Press, West Lafayette (1998)
3. Everett, M.G., Borgatti, S.P.: Analyzing clique overlap.Connections 21(1), 49-61 (1998)
4. Gregori, E., Lenzini, L., Orsini, C.: k-clique communities in the internet AS-level topology graph.In: SIMPLEX 2011 (2011)
5. Kumpula, J.M., Kivelä, M., Kaski, K., Saramäki, J.: Sequential algorithm for fast clique percolation.Phys.Rev.E 78(2), 026109 (2008)
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7. Tarjan, R.E., van Leeuwen, J.: Worst-case analysis of set union algorithms.J.ACM 31, 245-281 (1984)