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2018 IEEE 34th International Conference on Data Engineering (ICDE) (2018)
Paris, France
Apr 16, 2018 to Apr 19, 2018
ISSN: 2375-026X
ISBN: 978-1-5386-5520-7
pp: 701-712
Mining dense subgraphs on multi-layer graphs is an interesting problem, which has witnessed lots of applications in practice. To overcome the limitations of the quasi-clique-based approach, we propose d-coherent core (d-CC), a new notion of dense subgraph on multi-layer graphs, which has several elegant properties. We formalize the diversified coherent core search (DCCS) problem, which finds k d-CCs that can cover the largest number of vertices. We propose a greedy algorithm with an approximation ratio of 1 - 1/e and two search algorithms with an approximation ratio of 1/4. The experiments verify that the search algorithms are faster than the greedy algorithm and produce comparably good results as the greedy algorithm in practice. As opposed to the quasi-clique-based approach, our DCCS algorithms can fast detect larger dense subgraphs that cover most of the quasi-clique-based results.
approximation theory, data mining, graph theory, greedy algorithms, search problems

R. Zhu, Z. Zou and J. Li, "Diversified Coherent Core Search on Multi-Layer Graphs," 2018 IEEE 34th International Conference on Data Engineering (ICDE), Paris, France, 2018, pp. 701-712.
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