Nature-inspired optimization algorithms for community detection in complex networks: a review and future trends
作者： Dhuha Abdulhadi Abduljabbar , Siti Zaiton Mohd Hashim , Roselina Sallehuddin
DOI: 10.1007/S11235-019-00636-X
关键词:
摘要: Over the past couple of decades, research area network community detection has seen substantial growth in popularity, leading to a wide range researches literature. Nature-inspired optimization algorithms (NIAs) have given significant contribution solving problem by transcending limitations other techniques. However, due importance topic and its prominence many applications, information on it is scattered various journals, conference proceedings, patents, lacked focused-literature that synthesizes them single document. This review aims provide an overview NIAs their role problems. To achieve this goal, systematic study performed NIAs, followed historical statistical analysis involved. would lead identification future trends, as well discovery related challenges. provides guide for researchers identify new areas research, directing interest towards developing more effective frameworks context nature-inspired algorithms.
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