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A Spectral Clustering Algorithm Based on Hierarchical Method

  • Xiwei Chen
  • Li LiuEmail author
  • Dashi Luo
  • Guandong Xu
  • Yonggang Lu
  • Ming Liu
  • Rongmin Gao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8316)

Abstract

Most of the clustering algorithms were designed to cluster the data in convex spherical sample space, but their ability was poor for clustering more complex structures. In the past few years, several spectral clustering algorithms were proposed to cluster arbitrarily shaped data in various real applications including image processing and web analysis. However, most of these algorithms were based on k-means, which is a randomized algorithm and makes the algorithm easy to fall into local optimal solutions. Hierarchical method could handle the local optimum well because it organizes data into different groups at different levels. In this paper, we propose a novel clustering algorithm called spectral clustering algorithm based on hierarchical clustering (SCHC), which combines the advantages of hierarchical clustering and spectral clustering algorithms to avoid the local optimum issues. The experiments on both synthetic data sets and real data sets show that SCHC outperforms other six popular clustering algorithms. The method is simple but is shown to be efficient in clustering both convex shaped data and arbitrarily shaped data.

Keywords

Data mining Clustering Spectral clustering Hierarchical clustering 

Notes

Acknowledgement

This work was partially supported by the National Natural Science Foundation of China (grant no.61003240), the Scientific Research Foundation for the Returned Overseas Chinese Scholars(grant order no.44th), and the Opening Project of Guangdong Province Key Laboratory of Computational Science at the Sun Yat-sen University (grant year 2012).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Xiwei Chen
    • 1
  • Li Liu
    • 1
    Email author
  • Dashi Luo
    • 1
  • Guandong Xu
    • 2
  • Yonggang Lu
    • 1
  • Ming Liu
    • 3
  • Rongmin Gao
    • 4
  1. 1.School of Information Science and EngineeringLanzhou UniversityLanzhouPeople’s Republic of China
  2. 2.Advanced Analytics InstituteUniversity of Technology SydneyUltimoAustralia
  3. 3.School of Electrical and Information EngineeringThe University of SydneySydneyAustralia
  4. 4.School of PharmacyLanzhou UniversityLanzhouPeople’s Republic of China

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