Using Modified Periodicity Transform for Partially Periodic Pattern Mining

ASIA unversity > 資訊學院 > 資訊工程學系 > 博碩士論文 > Item 310904400/3924

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://asiair.asia.edu.tw/ir/handle/310904400/3924

题名:	Using Modified Periodicity Transform for Partially Periodic Pattern Mining
作者:	Tsai Meng-Shu
贡献者:	Department of Computer Science and Information Engineering
关键词:	time series analysis;partially periodic pattern mining;periodic pattern mining;data mining
日期:	2004
上传时间:	2009-11-18 13:13:11 (UTC+0)
出版者:	Asia University
摘要:	Numerous efforts had been made on periodic pattern mining in the past years. The problem of partially periodic pattern mining is similar to that of periodic pattern mining; however, the occurrences of patterns in sequences are different. Unlike periodic patterns, partially periodic patterns usually yield a result of period missing and/or shifting. Many approaches to partially periodic pattern mining had been proposed in the literature, but did not reach a satisfactory result in terms of computation time and memory accessibility. Besides, most approaches require given patterns for the mining tasks. On the basis of periodicity transforms, the modified periodicity transforms (MPT) and modified periodicity transforms without candidate pattern (MPT_NNC) are proposed in the study for discovering partially periodic patterns in sequences. Moreover, an efficient method for automatic generation of candidate patterns without giving domain knowledge is proposed as well. It is based on the location and possibility of the basis elements in a sequence and can be regarded as an auxiliary approach to the MPT and MPT_NNC algorithms.
显示于类别:	[資訊工程學系] 博碩士論文

文件中的档案:

档案	大小	格式	浏览次数
	0Kb	Unknown	330	检视/开启

在ASIAIR中所有的数据项都受到原著作权保护.

数据加载中.....