Detecting Overlapping Link Communities by Finding Local Minima of a Cost Function with a Memetic Algorithm. Part 1: Problem and Method
arXiv:1501.05139
Abstract
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.
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 4
References in corpus (6)
- Detecting the overlapping and hierarchical community structure of complex networks
- Line Graphs, Link Partitions and Overlapping Communities
- Community detection in networks: Structural communities versus ground truth
- Identification of overlapping communities and their hierarchy by locally calculating community-changing resolution levels
- Identification of Overlapping Communities by Locally Calculating Community-Changing Resolution Levels
- Evaluating Overlapping Communities with the Conductance of their Boundary Nodes