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Authors: Randa Boukabene ; Fatima Tayeb and Narimene Dakiche

Affiliation: Laboratoire des Methodes de Conception de Systèmes (LMCS), Ecole Nationale Supérieure d’Informatique (ESI), BP 68M - 16270 Oued Smar, Alger, Algeria

Keyword(s): Social Networks, Community Detection, Cuckoo Search Optimization, Modularity, Random Key.

Abstract: Social network analysis is a prominent and thriving research field, with community detection being a particularly active area of study. In this study, we propose a cuckoo search-based approach for identifying the best network partitions by maximizing the modularity function. The proposed algorithm combines wisely the continuous nature of the standard cuckoo search algorithm with the discrete nature of the community detection problem to achieve the best results. Firstly, the algorithm incorporates the random key representation, which operates in a continuous space. This representation enables the algorithm to perform global and local walks, enabling both exploration and exploitation within the search space. Secondly, the algorithm utilizes the locus-based representation to handle the discrete aspect of the community detection problem. Experiments on both synthetic and real-world networks demonstrate the effectiveness and efficiency of our proposed algorithm.

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Paper citation in several formats:
Boukabene, R., Tayeb, F. and Dakiche, N. (2023). Improved Random Key Cuckoo Search Optimization Algorithm for Community Detection in Social Networks. In Proceedings of the 19th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-672-9; ISSN 2184-3252, SciTePress, pages 113-120. DOI: 10.5220/0012202000003584

@conference{webist23,
author={Randa Boukabene and Fatima Tayeb and Narimene Dakiche},
title={Improved Random Key Cuckoo Search Optimization Algorithm for Community Detection in Social Networks},
booktitle={Proceedings of the 19th International Conference on Web Information Systems and Technologies - WEBIST},
year={2023},
pages={113-120},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012202000003584},
isbn={978-989-758-672-9},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Web Information Systems and Technologies - WEBIST
TI - Improved Random Key Cuckoo Search Optimization Algorithm for Community Detection in Social Networks
SN - 978-989-758-672-9
IS - 2184-3252
AU - Boukabene, R.
AU - Tayeb, F.
AU - Dakiche, N.
PY - 2023
SP - 113
EP - 120
DO - 10.5220/0012202000003584
PB - SciTePress

- Science and Technology Publications, Lda.
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