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A K-Nearest Neighbor Algorithm for Categorical Sequence Data

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2005, 10(2), pp.215-222
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Seung-Joon Oh 1

1경기과학기술대학교

Candidate

ABSTRACT

TRecently, there has been enormous growth in the amount of commercial and scientific data, such as protein sequences, retail transactions, and web-logs. Such datasets consist of sequence data that have an inherent sequential nature. In this paper, we study how to classify these sequence datasets. There are several kinds techniques for data classification such as decision tree induction, Bayesian classification and K-NN etc. In our approach, we use a K-NN algorithm for classifying sequences. In addition, we propose a new similairty measure to compute the similarity between two sequences and an efficient method for measuring similarity.

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