Seeding for pervasively overlapping communities

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چکیده

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Seeding for pervasively overlapping communities

In some social and biological networks, the majority of nodes belong to multiple communities. It has recently been shown that a number of the algorithms specifically designed to detect overlapping communities do not perform well in such highly overlapping settings. Here, we consider one class of these algorithms, those which optimize a local fitness measure, typically by using a greedy heuristi...

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Efficiently detecting overlapping communities using seeding and semi-supervised learning

Seeding then expanding is a commonly used scheme to discover overlapping communities from a network. Most seeding methods existed are either too complexity to scale to large networks or too simple to select high-quality seeds; and the non-principled functions used by most expanding methods lead the poor performances when applied them on diverse networks. This paper proposes a new method which t...

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In network analysis, a community is typically considered of as a group of nodes with a great density of edges among themselves and a low density of edges relative to other network parts. Detecting a community structure is important in any network analysis task, especially for revealing patterns between specified nodes. There is a variety of approaches presented in the literature for overlapping...

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Identifying overlapping communities using multi-agent collective intelligence

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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 ...

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ژورنال

عنوان ژورنال: Physical Review E

سال: 2011

ISSN: 1539-3755,1550-2376

DOI: 10.1103/physreve.83.066107