Zhengyu Hua
ABSTRACT
(α, β)-core decomposition is a fundamental problem in graph analysis, and has been widely adopted for anomaly detection and online group recommendation. Nevertheless,(α, β)-core model only considers the distance-1 neighborhood, which makes it unable to provide more fine-grained structure information. Motivated by this,(α, β, h)-core model is proposed in this paper, which requires the vertices in one/another part has at least α /β other vertices at distance not greater than h within the subgraph. Due to the distance-h neighborhoods are considered, the new model can identify more fine-grained structure information, which also makes the corresponding (α, β, h)-core decomposition challenging. To address this problem, an efficient algorithm based on computation-sharing strategy is proposed and the time complexity is analyzed accordingly. Experimental results on eight real graphs demonstrate the effectiveness of the proposed model and efficiency of the proposed algorithms.
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Index Terms
- Efficient distance-generalized (α, β)-core decomposition on bipartite graphs
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