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Enhancing Group Search Optimization with Node Similarities for Detecting Communities

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Intelligent Systems Technologies and Applications 2016 (ISTA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 530))

Abstract

Recent research in nature based optimization algorithms is directed towards analyzing domain specific enhancements for improving results optimality. This paper proposes an Enhanced Group Search Optimization (E-GSO) algorithm, a variant of the nature based Group Search Optimization (GSO) algorithm to detect communities in complex networks with better modularity and convergence. E-GSO enhances GSO by merging node similarities in its basic optimization process for fixing co-occurrences of highly similar nodes. This leads to avoidance of random variations on fixed node positions, enabling faster convergence to communities with higher modularity values. The communities are thus evolved in an unsupervised manner using an optimized search space. The experimental results established using real/synthetic network datasets support the effectiveness of the proposed E-GSO algorithm.

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Author information

Authors and Affiliations

  1. Kalindi College, University of Delhi, Delhi, India

    Nidhi Arora

  2. Dyal Singh College, University of Delhi, Delhi, India

    Hema Banati

Authors
  1. Nidhi Arora
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  2. Hema Banati
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Corresponding author

Correspondence to Nidhi Arora .

Editor information

Editors and Affiliations

  1. Dept. of CS, School of Science, University of Salamanca Dept. of CS, School of Science, Salamanca, Spain

    Juan Manuel Corchado Rodriguez

  2. Machine Intelligence Unit, Indian Statistical Institute Machine Intelligence Unit, Kolkata, India

    Sushmita Mitra

  3. and Management – Kerala (IIITM-K), Indian Inst. of Information Technology and Management – Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  4. King Fahd Univ of Petroleum and Minerals , Dhahran, Saudi Arabia

    El-Sayed El-Alfy

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Arora, N., Banati, H. (2016). Enhancing Group Search Optimization with Node Similarities for Detecting Communities. In: Corchado Rodriguez, J., Mitra, S., Thampi, S., El-Alfy, ES. (eds) Intelligent Systems Technologies and Applications 2016. ISTA 2016. Advances in Intelligent Systems and Computing, vol 530. Springer, Cham. https://doi.org/10.1007/978-3-319-47952-1_24

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  • DOI: https://doi.org/10.1007/978-3-319-47952-1_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47951-4

  • Online ISBN: 978-3-319-47952-1

  • eBook Packages: EngineeringEngineering (R0)

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