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The Scientific World Journal
Volume 2014, Article ID 926020, 11 pages
Research Article

A Fast Density-Based Clustering Algorithm for Real-Time Internet of Things Stream

Department of Information System, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia

Received 10 April 2014; Accepted 18 May 2014; Published 19 June 2014

Academic Editor: Xudong Zhu

Copyright © 2014 Amineh Amini et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [8 citations]

The following is the list of published articles that have cited the current article.

  • Amineh Amini, Hadi Saboohi, Tutut Herawan, and Teh Ying Wah, “MuDi-Stream: A Multi Density Clustering Algorithm for Evolving Data Stream,” Journal of Network and Computer Applications, 2014. View at Publisher · View at Google Scholar
  • Giandomenico Spezzano, Andrea Vinci, Giandomenico Spezzano, and Andrea Vinci, “Pattern Detection in Cyber-Physical Systems,” 6Th International Conference On Ambient Systems, Networks And Technologies (Ant-2015), The 5Th International Conference On Sustainable Energy Information Technology (Seit-2015), vol. 52, pp. 1016–1021, 2015. View at Publisher · View at Google Scholar
  • Narsimha, and Shahina Parveen, “Optimized clustering with statistical-based local model for replica management in DDM over grid,” Advances in Intelligent Systems and Computing, vol. 465, pp. 23–33, 2016. View at Publisher · View at Google Scholar
  • Giordano Mancini, and Balasubramanian Chandramouli, “Cherry-picking functionally relevant substates from long md trajectories using a stratified sampling approach,” Theoretical Biology Forum, vol. 109, no. 1-2, pp. 49–59, 2016. View at Publisher · View at Google Scholar
  • A. A Haneen, A. Noraziah, and Mohd Helmy Abd Wahab, “A Review on Data Stream Classification,” Journal of Physics: Conference Series, vol. 1018, pp. 012019, 2018. View at Publisher · View at Google Scholar
  • Saroj Kr Biswas, Debashree Devi, and Manomita Chakraborty, “A Hybrid Case Based Reasoning Model for Classification in Internet of Things (IoT) Environment,” Journal of Organizational and End User Computing, vol. 30, no. 4, pp. 104–122, 2018. View at Publisher · View at Google Scholar
  • M. Bharti, R. Kumar, and S. Saxena, “Clustering-based resource discovery on Internet-of-Things,” International Journal of Communication Systems, pp. e3501, 2018. View at Publisher · View at Google Scholar
  • Matthias Carnein, and Heike Trautmann, “Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms,” Business & Information Systems Engineering, 2019. View at Publisher · View at Google Scholar