Abstract
In this paper, we investigate the challenge of increasing the size of graphs for finding γ-quasi-cliques. We propose an algorithm based on MapReduce programming model. In the proposed solution, we use some known techniques to prune unnecessary and inefficient parts of search space and divides the massive input graph into smaller parts. Then the data for processing each part is sent to a single computer. The evaluation shows that we can substantially reduce the time for large graphs and besides there is no limit for graph size in our algorithm.
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Khosraviani, A., Sharifi, M. (2011). A Distributed Algorithm for γ-Quasi-Clique Extractions in Massive Graphs. In: Pichappan, P., Ahmadi, H., Ariwa, E. (eds) Innovative Computing Technology. INCT 2011. Communications in Computer and Information Science, vol 241. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27337-7_40
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DOI: https://doi.org/10.1007/978-3-642-27337-7_40
Publisher Name: Springer, Berlin, Heidelberg
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