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Mathematical Problems in Engineering
Volume 2013, Article ID 295067, 9 pages
Research Article

Smooth Splicing: A Robust SNN-Based Method for Clustering High-Dimensional Data

1School of Mathematics, Hefei University of Technology, Hefei 230009, China
2Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China
3Department of Automation, University of Science and Technology of China, Hefei 230027, China

Received 8 October 2012; Revised 20 May 2013; Accepted 20 May 2013

Academic Editor: Jun Zhao

Copyright © 2013 JingDong Tan and RuJing Wang. 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 [3 citations]

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

  • Jingdong Tan, and Rujing Wang, “Mining frequent k-edge-connected subgraphs,” 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), pp. 1312–1317, . View at Publisher · View at Google Scholar
  • Asieh Ghanbarpour, and Behrooz Minaei, “EXDBSCAN: An extension of DBSCAN to detect clusters in multi-density datasets,” 2014 Iranian Conference on Intelligent Systems (ICIS), pp. 1–5, . View at Publisher · View at Google Scholar
  • Kai Ming Ting, Bo Chen, Takashi Washio, and Ye Zhu, “Local contrast as an effective means to robust clustering against varying densities,” Machine Learning, vol. 107, no. 8-10, pp. 1621–1645, 2018. View at Publisher · View at Google Scholar