Truss Decomposition in Massive Networks

Jia Wang; James Cheng

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arXiv · 1205.6693

Truss Decomposition in Massive Networks

Jia Wang·James Cheng

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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.

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BibTeX RIS

Jia Wang, James Cheng. 2012-05-30. Truss Decomposition in Massive Networks. https://arxiv.org/abs/1205.6693

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