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• W2912293861 abstract "As recent work demonstrated, the task of identifying communities in networks can be considered analogous to the classical problem of decoding messages transmitted along a noisy channel. We leverage this analogy to develop a community detection method directly inspired by a standard and widely-used decoding technique. We further simplify the algorithm to reduce the time complexity from quadratic to linear. We test the performance of the original and reduced versions of the algorithm on artificial benchmarks with pre-imposed community structure, and on real networks with annotated community structure. Results of our systematic analysis indicate that the proposed techniques are able to provide satisfactory results." @default.
• W2912293861 created "2019-02-21" @default.
• W2912293861 creator A5022491810 @default.
• W2912293861 creator A5048471401 @default.
• W2912293861 date "2019-03-27" @default.
• W2912293861 modified "2023-09-24" @default.
• W2912293861 title "Error-correcting decoders for communities in networks" @default.
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• W2912293861 doi "https://doi.org/10.1007/s41109-019-0114-7" @default.
• W2912293861 hasPublicationYear "2019" @default.
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