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- W2989378258 abstract "The existence of communities in various complex networks is ubiquitous in all aspects of people’s living. Hence, it is crucial to uncover communities accurately, which is one of the hottest research areas in the field of network analysis. Particularly, complex networks are usually in continuous change so that it is more realistic to uncover dynamic communities. In this study, an algorithm based on node contribution for uncovering dynamic communities is proposed. Firstly, the seed nodes are selected via node local fitness in the network, thus guaranteeing that the selected seeds are central nodes of communities. Secondly, a static algorithm is used to obtain communities in initial snapshot of the network. Finally, node contribution is proposed to incrementally uncover communities in non-initial snapshots of the network. The experimental results reveal that our method outperforms all other comparison algorithms in both artificial and real datasets." @default.
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- W2989378258 date "2019-01-01" @default.
- W2989378258 modified "2023-10-16" @default.
- W2989378258 title "A Local Dynamic Community Detection Algorithm Based on Node Contribution" @default.
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- W2989378258 doi "https://doi.org/10.1007/978-981-15-1377-0_28" @default.
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