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    SYSTEM AND METHOD FOR DISCOVERING PATTERNS WITH NOISE
    1.
    发明公开
    SYSTEM AND METHOD FOR DISCOVERING PATTERNS WITH NOISE 审中-公开
    系统和方法来发现噪音中模式

    公开(公告)号：EP1380004A4

    公开(公告)日：2008-07-23

    申请号：EP02715182

    申请日：2002-03-22

    Applicant: IBM

    Inventor： WANG WEI ,  YANG JIONG ,  YU PHILIP SHI-LUNG

    IPC: G06F19/24 ,  G06K9/00 ,  G06K9/68

    CPC classification number: G06K9/62 ,  G06F19/24 ,  Y10S707/99936

    Abstract: A system and method for determining patterns in a data sequence (Fig. 1) constructs a compatibility matrix (100) which provides a probability between an actual occurrence of an item and an observed occurrence of that or another item between each item in the data sequence. Candidate patterns are generated (201). The candidate patterns include items in the data sequence. The candidate patterns are checked against the data sequence to determine a match value (203) based on the compatibility matrix, and significant matches are determined based on candidate patterns having the match value above a threshold (204).

    Data mining of weighted data
    2.
    发明专利
    Data mining of weighted data 未知

    公开(公告)号：GB2366024A

    公开(公告)日：2002-02-27

    申请号：GB0101503

    申请日：2001-01-22

    Applicant: IBM

    Inventor： YU PHILIP SHI-LUNG ,  WANG WEI ,  YANG JIONG

    IPC: G06F19/00 ,  G06F9/44 ,  G06F17/30 ,  G06N5/02 ,  G06N5/04 ,  G06F17/60

    Abstract: The traditional association rule problem is extended by allowing a weight to be associated with each item in a transaction to reflect interest/intensity of each item within the transaction. The weighted association rules from a set of tuple lists are discovered, where each tuple consists of an item and an associated weight and each tuple list consists of multiple tuples. The weighted association rules (WARs) are generated where some subset of items forms the consequent part of the rule (i.e., right hand side of the rule) and some other (non-overlapped) subset of items form the antecedent part of the rule (i.e., left hand side of the rule). The range of the weight value of each item is specified in the rule such that the number of tuples satisfying both the left hand side and right hand side of the rule exceeds a pre-specified support level (referred to as the support requirement) and the fraction of tuples satisfying the left hand side that also satisfy the right hand side exceeds a pre- specified confidence level (referred to as the confidence requirement).

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