A fast community detection algorithm based on coot bird metaheuristic optimizer in social networks. (September 2022)

• Record Type: Journal Article
• Authors: Koc, Ismail
• Is Part Of: Engineering applications of artificial intelligence. Volume 114(2022)
• Publication Date: 2022-09
• Subjects: Metaheuristic algorithms -- Community detection -- Discrete optimization -- Graph structures -- Social networks -- Modularity; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2022.105202
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: Community detection (CD) is critical to understanding complex networks. Researchers have made serious efforts to develop efficient CD algorithms in this sense. Since community detection is an NP-hard problem, utilizing metaheuristic algorithms is preferred instead of classical approaches in solving the problem. For this reason, in this study, six different metaheuristic algorithms called Archimedes optimization algorithm (AOA), Atom search optimization (ASO), Coot Bird Natural Life Model (COOT), Harris Hawks Optimization (HHO), Slime Mould Algorithm (SMA) and Arithmetic Optimization Algorithm (AROA) are used in the solution of CD problems and all of which have been proposed for solving continuous problems in recent years. Since the CD problem has a discrete structure, discrete versions of all the algorithms are produced, and then the proposed discrete algorithms are adapted to the problem. In addition, in the phase of evaluating the objective function of the problem, a fast approach based on CommunityID is proposed to minimize the time cost when solving the problem, and this approach is utilized in all the algorithms when calculating the fitness value. In the experimental studies, firstly, the novel discrete algorithms are compared with each other in terms of solution quality and time and according to these results, COOT becomes the most effective and very fast algorithm. Then, the results obtained by COOT are compared with those of important studies in the literature. When compared in terms of solution quality, it is seen that the COOT algorithm is more effective than the other algorithms. In addition, it is quite obvious that all of the proposed algorithms using the CommunityID- based approach are faster than the other algorithms in the literature in terms of time. As a result, it can be said that COOT can be an effective alternative method for dealing with CD problems. In addition, the approach based on CommunityID can also be utilized in larger networks to obtain remarkable solutions in a much shorter time.