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

ABSTRACT

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.

INDEX TERMS

approximation theory, data mining, graph theory, greedy algorithms, search problems

CITATION

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.

doi:10.1109/ICDE.2018.00069

CITATIONS