Data mining with time granules

机译：使用时间粒度进行数据挖掘

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摘要

Most of the existing studies only consider different item lifespans to find general temporal association rules, and this may neglect some useful information. In this paper, the concept of a hierarchy of time periods is considered and a new kind of rules, called hierarchical temporal rules, is proposed. The lifespan of an item in a time granule is calculated from its first appearance time to the end time in the time granule. The experimental results on a simulation dataset show the performance of the proposed algorithm under the new item lifespan.

机译：现有的大多数研究仅考虑不同的物品寿命来找到一般的时间关联规则，而这可能会忽略一些有用的信息。本文考虑了时间层次结构的概念，提出了一种新的规则，称为时间层次规则。时间颗粒中项目的寿命是从其首次出现时间到时间颗粒中的结束时间来计算的。在模拟数据集上的实验结果表明了该算法在新产品寿命下的性能。

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来源
《2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining》|2012年|673-677|共5页
会议地点 Taipei(CT)
作者
Hong Tzung-Pei; Lan Guo-Cheng; Wu Pei-Shan; Wang Shyue-Liang;
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作者单位

Department of Computer Science and Information Engineering, National University of Kaohsiung, Taiwanc;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Data mining; a hierarchy of time granules; association-rule mining; item lifespan; temporal association rules;

机译：数据挖掘;时间粒度层次;关联规则挖掘;项目寿命;时间关联规则;;

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2. Mining Hidden Granules From Relational Database Systems For Recommendation [J] . V.Ajitha, Paulrajan Rajkumar Australian Journal of Basic and Applied Sciences . 2015,第2015期

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3. From data point timelines to a well curated data set, data mining of experimental data and chemical structure data from scientific articles, problems and possible solutions [J] . Ruusmann V., Maran U. Journal of Computer-Aided Molecular Design . 2013,第7期

机译：从数据点时间表到精心挑选的数据集，从科学文章，问题和可能的解决方案中挖掘实验数据和化学结构数据的数据
4. Data Mining with Time Granules [C] . Tzung-Pei Hong, Guo-Cheng Lan, Pei-Shan Wu, International Conference on New Trends in Information Science, Service Science and Data Mining . 2012

机译：数据挖掘与时间颗粒
5. Pattern-Based Data Mining on Diverse Multimedia and Time Series Data. [D] . Campana, Bilson Jake. 2012

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6. Addressing Big Data Time Series: Mining Trillions of Time Series Subsequences Under Dynamic Time Warping [O] . THANAWIN RAKTHANMANON, BILSON CAMPANA, ABDULLAH MUEEN, -1

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7. Granule mining oriented data warehousing model for representations of multidimensional association rules [O] . Wanzhong Yang, Yuefeng Li, Jingtong Wu, 2008

机译：面向粒度挖掘的数据仓库模型，用于多维关联规则的表示

Data mining with time granules

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