Community detection in complex networks using stacked autoencoders and crow search algorithm
The presence of community structures in complex networks reveals meaningful insights about such networks and their constituent entities. Finding groups of related nodes based on mutual interests, common features, objectives, or interactions in a network is known as community detection. In this paper, we propose a novel Stacked Autoencoder-based deep learning approach augmented by the Crow Search Algorithm (CSA)-based k-means clustering algorithm to uncover community structure in complex networks. As per our approach, firstly, we generate a modularity matrix for the input graph. The modularity matrix is then passed through a series of stacked autoencoders to reduce the dimensionality of the matrix while preserving the topology of the network and improving the computational time of the proposed algorithm. The obtained matrix is then provided as an input to a modified k-means clustering algorithm augmented with the crow search optimization to detect the communities. We use Crow Search Algorithm-based optimization to generate the initial centroids for the k-means algorithm instead of generating them randomly. We perform extensive experimental analysis on several real-world and synthetic datasets and evaluate various performance metrics. We compare the results obtained by our algorithm with several traditional and contemporary community detection algorithms. The obtained results reveal that our proposed method achieves commendable results.
History
Publisher
SpringerVersion
- AM (Accepted Manuscript)
Citation
Kumar, S., Mallik, A., & Sengar, S. S. (2023) 'Community detection in complex networks using stacked autoencoders and crow search algorithm', The Journal of Supercomputing, 79(3), 3329-3356.Print ISSN
0920-8542Electronic ISSN
1573-0484Cardiff Met Affiliation
- Cardiff School of Technologies
Cardiff Met Authors
Sandeep Singh SengarCopyright Holder
- © The Publisher
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Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.Language
- en