An Efficient Algorithm for Community Detection using Multi Objective Evolutionary Algorithm

Community structure is one of the most important properties in social networks. Social networks are active on the assembly line and each batch of Internet users with certain characteristics come together. Social networks and social media so they know that it is possible to achieve a new way of communicating and sharing content on the Internet have created. Social network concept that the design in virtual space, in real space as well as a sense of community. Social Networking like any social network is made up of community and human relationships in society. The proposed method includes precise mathematical methods and is approximate and innovative, adaptable and efficient. The nature of the problem is due to the nature of intelligent behaviour and genetic algorithm based on random behaviour of its elements, Genetic algorithm optimization combined with modularity concept that is one of swarm intelligence is used in this research. Therefore, in this study we used a genetic multi-objective optimization algorithm to achieve an increase in modularity. This approach by two criteria, coefficient Do was silhouette index and the quality of the proposed method is determined.

Keywords:

Social Discovery , multi-objective optimization , centralized node , Social Network