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    Detecting Overlapping Link Communities by Finding Local Minima of a Cost Function with a Memetic Algorithm. Part 1: Problem and Method

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    We propose an algorithm for detecting communities of links in networks which uses local information, is based on a new evaluation function, and allows for pervasive overlaps of communities. The complexity of the clustering task requires the application of a memetic algorithm that combines probabilistic evolutionary strategies with deterministic local searches. In Part 2 we will present results of experiments with with citation networks.Comment: 11 pages, 2 figures, 2 appendixes; there is some overlap in Appendix A with our earlier preprint arXiv:1206.3992; we have added a reference and revised arguments in sections 1, 3, and
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