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A Hierarchical Clustering Algorithm Using Extended Sequence Element-based Similarity Measure

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2006, 11(5), pp.321-328
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Seung-Joon Oh 1

1경기과학기술대학교

Candidate

ABSTRACT

Recently, there has been enormous growth in the amount of commercial and scientific data. Such datasets consist of sequence data that have an inherent sequential nature. However, only a few of the existing clustering algorithms consider sequentiality. This study presents a similarity measure and a method for clustering such sequence datasets. Especially, we present an extended concept of the measure of similarity, which considers various conditions. Using a splice dataset, we show that the quality of clusters generated by our proposed clustering algorithm is better than that of clusters produced by traditional clustering algorithms.

Citation status

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