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  • 标题:A Self-adaptive Spectral Clustering Based on Geodesic Distance and Shared Nearest Neighbors
  • 本地全文:下载
  • 作者:Chunmiao Yuan ; Kaixiang Fan ; Xuemei Sun
  • 期刊名称:International Journal of Hybrid Information Technology
  • 印刷版ISSN:1738-9968
  • 出版年度:2016
  • 卷号:9
  • 期号:4
  • 页码:417-426
  • DOI:10.14257/ijhit.2016.9.4.36
  • 出版社:SERSC
  • 摘要:Spectral clustering is a method of subspace clustering which is suitable for the data of any shape and converges to global optimal solution. By combining concepts of shared nearest neighbors and geodesic distance with spectral clustering, a self-adaptive spectral clustering based on geodesic distance and shared nearest neighbors was proposed. Experiments show that the improved spectral clustering algorithm can fully take into account the information of neighbors, but also measure the exact distance and better process the geodetic data.
  • 关键词:Spectral clustering; Shared nearest neighbors; Geodesic distance; Subspace ; clustering
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