Truss decomposition in massive networks

Abstract

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.