| 挖掘多粒度时间下异步周期的模式 |
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| 引用本文： | 夏卓群,程昱,梁涤青.挖掘多粒度时间下异步周期的模式[J].计算机应用,2006,26(12):2985-2987. |
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| 作者姓名： | 夏卓群 程昱 梁涤青 |
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| 作者单位： | 1. 长沙理工大学,计算机与通信工程学院,湖南,长沙,410076
2. 浙江大学,计算机科学与技术学院,浙江,杭州,310027 |
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| 摘 要： | 把异步周期和多时间粒度下的时态模型结合起来研究,并利用异步周期的特点提出了一种有效的挖掘算法。算法先找到所有的有效时间节，再通过有效时间节求出最长的有效时间段。实验表明所提出的算法是稳定而有效的。
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| 关 键 词： | 数据挖掘 异步周期 多粒度 时间序列 |
| 文章编号： | 1001-9081（2006）12-2985-03 |
| 收稿时间： | 2006-06-12 |
| 修稿时间： | 2006-06-122006-09-01 |
Discovery of asynchronous periodic patterns with multiple granularities |
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| XIA Zhuo-qun,CHENG Yu,LIANG Di-qing.Discovery of asynchronous periodic patterns with multiple granularities[J].journal of Computer Applications,2006,26(12):2985-2987. |
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| Authors: | XIA Zhuo-qun CHENG Yu LIANG Di-qing |
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| Affiliation: | 1. College of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha Hunan 410076, China; 2. College of Computer Science, Zhejiang Gongshang University, Hangzhou Zhejiang 310035, China |
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| Abstract: | An algorithm for efficient mining of asynchronous periodic patterns with multiple granularities by exploring some interesting properties related to asynchronous periodicity was proposed. The algorithm generated all valid time section at first, and then found the longest valid time segment by using valid time section. The performance study shows that the proposed method is stable and efficient. |
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| Keywords: | data mining asynchronous periodicity muhiple granularities time series |
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