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[Author] Myeong-Seon GIL(1hit)

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  • Linear Detrending Subsequence Matching in Time-Series Databases

    Myeong-Seon GIL  Yang-Sae MOON  Bum-Soo KIM  

     
    LETTER-Artificial Intelligence, Data Mining

      Vol:
    E94-D No:4
      Page(s):
    917-920

    Every time-series has its own linear trend, the directionality of a time-series, and removing the linear trend is crucial to get more intuitive matching results. Supporting the linear detrending in subsequence matching is a challenging problem due to the huge number of all possible subsequences. In this paper we define this problem as the linear detrending subsequence matching and propose its efficient index-based solution. To this end, we first present a notion of LD-windows (LD means linear detrending). Using the LD-windows we then present a lower bounding theorem for the index-based matching solution and show its correctness. We next propose the index building and subsequence matching algorithms. We finally show the superiority of the index-based solution.