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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/35247


    Title: 挖掘模糊時間序列型樣
    Other Titles: Mining fuzzy time sequential patterns
    Authors: 廖珮妤;Liao, Pei-yu
    Contributors: 淡江大學資訊工程學系碩士班
    林丕靜;Lin, Nancy Pei-ching
    Keywords: 序列型樣;階層式分群法;模糊數;模糊時間區間;Sequential patterns;Hierarchical clustering;Fuzzy number;Fuzzy time interval
    Date: 2007
    Issue Date: 2010-01-11 06:15:30 (UTC+8)
    Abstract:   挖掘序列型樣是資料挖掘中一項重要的技術,主要用於找出序列資料庫中的頻繁子序列。一般挖掘序列型樣的演算法大多能正確找出頻繁項目集之間的發生先後順序,但對於其出現前後的間隔時間卻無法加以描述。
      為了有效解決此一問題,本研究結合階層式分群法與模糊數的概念,提出一個挖掘模糊時間序列型樣的演算法,不僅可以挖掘出序列資料庫中所有頻繁項目及其出現的順序關係,更可將其出現的間隔時間以合理的方式表示。
    An important task of sequential patterns mining is to discover frequent sequential patterns in a sequence database. Conventional sequential patterns only reveal the order of items, information about time intervals between successive by occurred items has not been determined.
    In this paper, we proposed an algorithm called fuzzy time sequential pattern mining (FTSP). We use the hierarchical clustering technique to cluster the time intervals between successive itemsets, and define a fuzzy number to each time cluster to compute the fuzzy support, and then we have mined the frequent fuzzy time sequential patterns.
    Fuzzy time sequential patterns mining, reveals not only the order of items, but also the time intervals between successive items.
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Thesis

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