Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities
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Abstract
Many complex networks display a mesoscopic structure with groups of nodes sharing many links with the other nodes in their group and comparatively few with nodes of different groups. This feature is known as community structure and encodes precious information about the organization and the function of the nodes. Many algorithms have been proposed but it is not yet clear how they should be tested. Recently we have proposed a general class of undirected and unweighted benchmark graphs, with heterogeneous distributions of node degree and community size. An increasing attention has been recently devoted to develop algorithms able to consider the direction and the weight of the links, which require suitable…
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Topics
Keywords
- Benchmark (surveying)
- Modularity (biology)
- Computer science
- Node (physics)
- Community structure
- Feature (linguistics)
- Theoretical computer science
- Clique percolation method
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