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Alatas, Bilal
- Overlapping Community Detection in Social Networks Using Parliamentary Optimization Algorithm
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1 Firat University, Department of Software Engineering, Elazig, TR
1 Firat University, Department of Software Engineering, Elazig, TR
Source
International Journal of Computer Networks and Applications, Vol 2, No 1 (2015), Pagination: 12-19Abstract
Parallel to growth of the Internet, social networks have become more attractive as a research topic in many different disciplines and many real systems can be denoted as a complex network. Identifying major clusters and community structures allow us to expose organizational principles in complex network such as web graphs and biological networks. It has been shown that communities are usually overlapping. Overlap is one of the characteristics of social networks, in which a person may belong to more than one social group. In recent years, overlapping community detection has attracted a lot of attention in the area of social networks applications. Many methods have been developed to solve overlapping community detection problem, using different tools and techniques. In this paper, one of the most recent social-based metaheuristic algorithm, Parliamentary Optimization Algorithm (POA), has been firstly proposed to discover overlapping communities in social networks.Keywords
Social Networks, Overlapping Community Detection, Parliamentary Optimization Algorithm.Full Text
- Discovery of Multi-Objective Overlapping Communities within Social Networks Using a Socially Inspired Metaheuristic Algorithm
Abstract Views :207 |
PDF Views:0
Authors
Affiliations
1 Department of Software Engineering, Firat University, Elazig, TR
2 Department of Software Engineering, Firat University, Elazig, IN
1 Department of Software Engineering, Firat University, Elazig, TR
2 Department of Software Engineering, Firat University, Elazig, IN
Source
International Journal of Computer Networks and Applications, Vol 4, No 6 (2017), Pagination: 148-158Abstract
Frequently studied structural property of networks is community structure which is described as a group of users. User interactions inside the group are more than those outside the group. Communities in networks may be overlapped as users belong to multiple groups at once. This paper proposes a new socially inspired metaheuristic search and optimization algorithm, Parliamentary Optimization Algorithm (POA), to acquire promising solutions to overlapping community detection problems considering multiple objectives. The salient and unique feature of this work is that for the first time POA has been designed as a multi-objective search method for overlapping community detection. There is not any work about multi-objective overlapping community detection problem in the related literature. For this reason, simulation results of the proposed algorithm have not been compared with any results of works. The experimental studies on both artificial and real world social networks indicate that the POA ensures beneficial results for defining multi-objective overlapping community structure. A novel and interesting application area of POA has been introduced with this work. Parallel and distributed versions of social based POA with optimized parameters may also be efficiently designed and used for different social network problems.Keywords
Complex Networks, Computational Intelligence, Evolutionary Computation, Heuristic Algorithms.Full Text
References
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