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Looking into the possibility for designing normal distribution based dissimilarity measure to discover time profiled association patterns

机译:探讨设计基于正态分布的差异度量以发现时间剖析的关联模式的可能性

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This research addresses the design of a novel dissimilarity measure for mining similar patterns from time stamped temporal databases applying the concept of standard score and normal distribution. The basic idea behind the design of dissimilarity measure is to use and transform supports to z-space and compute the probability of z-score of temporal patterns. The probability is obtained using normal distribution chart. The objective has been to design a normal distribution based dissimilarity measure which can be used to discover all valid similarity-profiled temporal association patterns.
机译:这项研究解决了一种新的差异度度量的设计,该度量利用标准分数和正态分布的概念从带有时间戳的时态数据库中挖掘相似模式。差异度量的设计背后的基本思想是使用支持并将其转换为z空间并计算时间模式z分数的概率。使用正态分布图获得概率。目的是设计一种基于正态分布的差异度量,该度量可用于发现所有有效的相似度剖析的时间关联模式。

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