The input/output complexity of sorting and related problems
Communications of the ACM
Classifying molecular sequences using a linkage graph with their pairwise similarities
Theoretical Computer Science - Special issue: Genome informatics
Algorithm 457: finding all cliques of an undirected graph
Communications of the ACM
Massive Quasi-Clique Detection
LATIN '02 Proceedings of the 5th Latin American Symposium on Theoretical Informatics
On mining cross-graph quasi-cliques
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Main-memory triangle computations for very large (sparse (power-law)) graphs
Theoretical Computer Science
Graph Twiddling in a MapReduce World
Computing in Science and Engineering
Finding maximal cliques in massive networks by H*-graph
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
On triangulation-based dense neighborhood graph discovery
Proceedings of the VLDB Endowment
Counting triangles and the curse of the last reducer
Proceedings of the 20th international conference on World wide web
Efficient core decomposition in massive networks
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
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)
Fast algorithms for maximal clique enumeration with limited memory
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Triangle listing in massive networks
ACM Transactions on Knowledge Discovery from Data (TKDD) - Special Issue on the Best of SIGKDD 2011
Fast algorithms for maximal clique enumeration with limited memory
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Large scale cohesive subgraphs discovery for social network visual analysis
Proceedings of the VLDB Endowment
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
TF-Label: a topological-folding labeling scheme for reachability querying in a large graph
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Redundancy-aware maximal cliques
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Top-K structural diversity search in large networks
Proceedings of the VLDB Endowment
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The k-truss is a type of cohesive subgraphs proposed recently for the study of networks. While the problem of computing most cohesive subgraphs is NP-hard, there exists a polynomial time algorithm for computing k-truss. Compared with k-core which is also efficient to compute, k-truss represents the "core" of a k-core that keeps the key information of, while filtering out less important information from, the k-core. However, existing algorithms for computing k-truss are inefficient for handling today's massive networks. We first improve the existing in-memory algorithm for computing k-truss in networks of moderate size. Then, we propose two I/O-efficient algorithms to handle massive networks that cannot fit in main memory. Our experiments on real datasets verify the efficiency of our algorithms and the value of k-truss.