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- W3145483502 abstract "Extracting dense structures in a social network is a fundamental task in graph mining and can find many real-world applications. The temporal social network augments the conventional social network with the temporal dimension, and extracting dense structures enables us to understand the period of time for which the dense structures exist. In this paper, we propose the new notion of (L, K)-lasting core, which is a densely connected subgraph lasting for a sufficiently long period of time in the temporal social network. We propose a polynomial-time algorithm to obtain the maximum (L, K)-lasting core with various processing strategies to boost the efficiency. We conduct extensive experiments on multiple datasets to validate the effectiveness and efficiency of the proposed approach. The experimental results show that our proposed approaches outperform the other baseline approaches in terms of solution quality and efficiency." @default.
- W3145483502 created "2021-04-13" @default.
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- W3145483502 date "2021-01-01" @default.
- W3145483502 modified "2023-10-17" @default.
- W3145483502 title "Maximum (L, K)-Lasting Cores in Temporal Social Networks" @default.
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- W3145483502 doi "https://doi.org/10.1007/978-3-030-73216-5_23" @default.
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