Clustering of Complex Networks and Community Detection Using Group Search Optimization
This work addresses network analysis problems for researchers in evolutionary computing and data mining, but it is incremental as it applies an existing method to a new domain.
The paper applied the Group Search Optimization (GSO) algorithm to network clustering and community detection, testing it on five benchmark datasets and showing it to be competitive in accuracy and convergence speed.
Group Search Optimizer(GSO) is one of the best algorithms, is very new in the field of Evolutionary Computing. It is very robust and efficient algorithm, which is inspired by animal searching behaviour. The paper describes an application of GSO to clustering of networks. We have tested GSO against five standard benchmark datasets, GSO algorithm is proved very competitive in terms of accuracy and convergence speed.