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Bernard Dousset
Paul Sabatier University
Computer Science & IT Electrical & Electronics Engineering

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Bat-Cluster: A Bat Algorithm-based Automated Graph Clustering Approach Zakaria Boulouard; Amine El Haddadi; Fadwa Bouhafer; Anass El Haddadi; Lahcen Koutti; Bernard Dousset
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (441.083 KB) | DOI: 10.11591/ijece.v8i2.pp1122-1130

Abstract

Defining the correct number of clusters is one of the most fundamental tasks in graph clustering. When it comes to large graphs, this task becomes more challenging because of the lack of prior information. This paper presents an approach to solve this problem based on the Bat Algorithm, one of the most promising swarm intelligence based algorithms. We chose to call our solution, “Bat-Cluster (BC).” This approach allows an automation of graph clustering based on a balance between global and local search processes. The simulation of four benchmark graphs of different sizes shows that our proposed algorithm is efficient and can provide higher precision and exceed some best-known values.
Co-Authors Amine El Haddadi Anass El Haddadi Fadwa Bouhafer Lahcen Koutti Zakaria Boulouard