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- W2807153906 abstract "In this paper, we propose an improved version of an agglomerative hierarchical clustering algorithm that performs disjoint community detection in large-scale complex networks. The improved algorithm is achieved after replacing the local structural similarity used in the original algorithm, with the recently proposed Dynamic Structural Similarity. Additionally, the improved algorithm is extended to detect fuzzy and crisp overlapping community structure. The extended algorithm leverages the disjoint community structure generated by itself and the dynamic structural similarity measures, to compute a proposed membership probability function that defines the fuzzy communities. Moreover, an experimental evaluation is performed on reference benchmark graphs in order to compare the proposed algorithms with the state-of-the-art." @default.
- W2807153906 created "2018-06-13" @default.
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- W2807153906 date "2018-05-30" @default.
- W2807153906 modified "2023-09-27" @default.
- W2807153906 title "High-Quality Disjoint and Overlapping Community Structure in Large-Scale Complex Networks" @default.
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