The Simple Genetic Algorithm: Foundations and Theory
The Simple Genetic Algorithm: Foundations and Theory
On the use of divergence distance in fuzzy clustering
Fuzzy Optimization and Decision Making
A study on the impact of crowd-based voting schemes in the 'Eurovision' European contest
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Clustering avatars behaviours from virtual worlds interactions
Proceedings of the 4th International Workshop on Web Intelligence & Communities
Features selection from high-dimensional web data using clustering analysis
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
A genetic graph-based clustering algorithm
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
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Finding communities in networks is a hot topic in several research areas like social network, graph theory or sociology among others. This work considers the community finding problem as a clustering problem where an evolutionary approach can provide a new method to find overlapping and stable communities in a graph. We apply some clustering concepts to search for new solutions that use new simple fitness functions which combine network properties with the clustering coefficient of the graph. Finally, our approach has been applied to the Eurovision contest dataset, a well-known social-based data network, to show how communities can be found using our method.