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  • 标题:A Representative Set Method for Symbolic Sequence Clustering,
  • 本地全文:下载
  • 作者:Kozarzewski Bohdan
  • 期刊名称:Computational Methods in Science and Technology
  • 印刷版ISSN:1505-0602
  • 出版年度:2013
  • 卷号:19
  • 期号:2
  • 页码:99-105
  • DOI:10.12921/cmst.2013.19.02.99-105
  • 出版社:Poznan Supercomputing and Networking Center
  • 摘要:

    Sequence decomposition into a set of consecutive, distinct subsequences is crucial for symbolic sequence analysis. It reduces significantly the reference base of the recorded sequence for further retrieval and allows for original similarity and membership measures of the sequences. The introduced measures are a start point to a new algorithm for clustering sequences into groups of similar individuals. Algorithms that use the concept of a representative set achieved relatively good clustering results. The representative set that we have introduced is precisely and uniquely defined in contrast to that used in other applications.

  • 关键词:clustering; representative set; similarity and membership measures
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