计算机科学 ›› 2012, Vol. 39 ›› Issue (6): 166-169.

• 数据库与数据挖掘 • 上一篇    下一篇

一种基于极大团的关键时间段挖掘方法

王宁,杨扬,巩华荣,赵耀培,孟坤   

  1. (北京科技大学计算机与通信工程学院 北京100083) (烟台工程职业技术学院机电工程系 烟台264006)(山东省工会管理干部学院科研处 济南250100)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Mining Method of Key Time Interval Based on Maximum Clique

  • Online:2018-11-16 Published:2018-11-16

摘要: 针对带有时间属性的海量事务处理问题,提出了一种求最大相关性的最小时间区间(关键时间段KTI)的算法。通过利用极大团把海量的数据项进行有效的划分,降低了后续数据挖掘和决策选择的复杂度。针对特定的含有时间参量的极大团,通过寻找关键时间段(KTI),提高了决策的准确度,同时可以减小分析数据的规模,降低对计算资源的需求。假设事务中各项出现的事件具有相同的概率分布,得到了一种寻找关键时间段(KTI)的算法。从理论上证明了算法的正确性,并对其进行了复杂度分析,通过实际数据验证了算法的可行性。

关键词: 数据挖掘,关联规则,时序逻辑,极大团,关键时间段(KTI) ,概率

Abstract: To efficiently process mass transactions with temporal attribute, the key time interval ( KhI),the minimum time interval reflecting correlation of items was introduced. A maximum clique based KTI mining algorithm was proposed, which reduces the complexity for information mining and decision making. Assuming the probability distribution of items is uniform for the target transaction, we stated an approach to find the KhI of the transaction and analyzed the correctness and complexity of the method. Experiments show that through considering the KTI of a clique, the candidates set impacting the accuracy of decision is reduced, and the resource consumption is saved mainly. In the end, we evaluated the feasibility of the proposed method in the real world use.

Key words: Data mining, Association rule, Time series logic, Maximum clique, Key time interval(KTI) , Probability

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