The input/output complexity of sorting and related problems
Communications of the ACM
Enumerating all connected maximal common subgraphs in two graphs
Theoretical Computer Science
Algorithm 457: finding all cliques of an undirected graph
Communications of the ACM
Efficiently Mining Maximal Frequent Itemsets
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Finding All Maximal Cliques in Dynamic Graphs
Computational Optimization and Applications
Proceedings of the sixteenth annual ACM symposium on Parallelism in algorithms and architectures
The worst-case time complexity for generating all maximal cliques and computational experiments
Theoretical Computer Science - Computing and combinatorics
Note: A note on the problem of reporting maximal cliques
Theoretical Computer Science
Large maximal cliques enumeration in sparse graphs
Proceedings of the 17th ACM conference on Information and knowledge management
A scalable, parallel algorithm for maximal clique enumeration
Journal of Parallel and Distributed Computing
Segmentation and Automated Social Hierarchy Detection through Email Network Analysis
Advances in Web Mining and Web Usage Analysis
A Distributed Algorithm to Enumerate All Maximal Cliques in MapReduce
FCST '09 Proceedings of the 2009 Fourth International Conference on Frontier of Computer Science and Technology
Finding maximal cliques in massive networks by H*-graph
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Efficient core decomposition in massive networks
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Listing all maximal cliques in large sparse real-world graphs
SEA'11 Proceedings of the 10th international conference on Experimental algorithms
Triangle listing in massive networks and its applications
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Finding maximal cliques in massive networks
ACM Transactions on Database Systems (TODS)
A new algorithm for enumerating all maximal cliques in complex network
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Truss decomposition in massive networks
Proceedings of the VLDB Endowment
Triangle listing in massive networks
ACM Transactions on Knowledge Discovery from Data (TKDD) - Special Issue on the Best of SIGKDD 2011
Truss decomposition in massive networks
Proceedings of the VLDB Endowment
Redundancy-aware maximal cliques
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
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Maximal clique enumeration (MCE) is a long-standing problem in graph theory and has numerous important applications. Though extensively studied, most existing algorithms become impractical when the input graph is too large and is disk-resident. We first propose an efficient partition-based algorithm for MCE that addresses the problem of processing large graphs with limited memory. We then further reduce the high cost of CPU computation of MCE by a careful nested partition based on a cost model. Finally, we parallelize our algorithm to further reduce the overall running time. We verified the efficiency of our algorithms by experiments in large real-world graphs.