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dc.contributor.author崔晓军
dc.contributor.author薛永生
dc.date.accessioned2017-11-14T03:19:30Z
dc.date.available2017-11-14T03:19:30Z
dc.date.issued2007-06-25
dc.identifier.citation计算机科学,2007,(06):191-194
dc.identifier.issn1002-137X
dc.identifier.otherJSJA200706051
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/156709
dc.description.abstract基于日历约束的时序关联规则挖掘由于其实用性,越来越受到研究者的关注。由于现实中用户很难对时间模式进行精确描述,因此基于模糊日历的时序关联规则挖掘更有现实意义。借助模糊概念和模糊运算,对时间区间的描述很容易实现。对于用户指定的日历模式,不同的时间区间可根据它们的隶属度具有不同的权重。在模糊日历代数的基础上,结合增量挖掘和累进计数的思想,本文提出了一种基于模糊日历约束的关联规则挖掘方法,理论分析和实验结果均表明,该算法是高效可行的。
dc.description.abstractResearch of mining calendar-based temporal association rules is attracting more and more attention because of it's practicability. But in real life,it is impossible for user to describe the time accurately, so fuzzy temporal association rules are more useful. Based on fuzzy calendar algebra and fuzzy operators, it is easy to describe desired temporal requirements. Time intervals may have different weights according to their membership functions. Integrated with the ideas of progression and increment ,this paper presents a algorithm called BFCTAR to mine fuzzy temporal association rules. Theory analysis and experiment results indicate that this algorithm is efficient and feasible.
dc.description.sponsorship福建省自然科学基金项目(A0310008);; 福建省高新技术研究开放计划重点项目(2003H043)。
dc.language.isozh_CN
dc.subject关联规则
dc.subject模糊数据挖掘
dc.subject模糊集
dc.subject模糊日历约束
dc.subjectAssociation rule,Fuzzy data mining, Fuzzy set, Fuzzy calendar constraint
dc.title基于模糊日历约束的时序关联规则挖掘
dc.title.alternativeDiscover Fuzzy Calendar-based Temporal Association Rules
dc.typeArticle


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