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Soft Computing

, Volume 23, Issue 21, pp 10717–10737 | Cite as

Dynamic clustering with binary social spider algorithm for streaming dataset

  • Urvashi Prakash ShuklaEmail author
  • Satyasai Jagannath Nanda
Methodologies and Application
  • 53 Downloads

Abstract

Technical advancement in various fields like social network, health instruments and astronomical devices poses massive capturing and sensing capacity that enables huge data generations. This demands substantial storage space and voluminous data processing capacity. Streaming data clustering imparts an efficient method for handling this dataset by extracting significant information. In this article, dynamic estimation of clusters in evolving data stream is designed by incorporating swarm optimization technique. One of the recently reported algorithms inspired from the social behavior of spiders residing in huge colonies is reformulated in binary domain. The main contribution is to use the binary social spider optimization (BSSO) for dynamic data clustering of evolving dataset (DSC-BSSO). The proposed work is able to prove efficiency and efficacy as compared to the other recent existing algorithms. BSSO is well tested on various benchmark unimodal, multimodal and binary optimization functions. Results are reported in terms of parametric and nonparametric. The testing of DSC-BSSO is also done on various streaming datasets in terms of time and memory complexity. The proposed work is able to obtain compact and well-separated clusters in less than one-fourth of a minute for about 10,000 samples.

Keywords

Dynamic clustering Page-Hinkley statistical test Social spider optimization Wilcoxon’s pair test 

Notes

Acknowledgements

The research work is funded by institute fellowship from Ministry of HRD, Govt. of India, to Urvashi P. Shukla to pursue her PhD work at MNIT Jaipur.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with animals or humans performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringMalaviya National Institute of Technology JaipurJaipurIndia

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