Mining association rules in interval-based temporal sequences

ZHU Tian1; BAI Shi-xue2; WANG Bai1; WU Bin1

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Mining association rules in interval-based temporal sequences

更新时间：2024-10-14

- Mining association rules in interval-based temporal sequences
- Vol. 30, Issue 8, Pages: 112-115(2009)
- 作者机构：
  
  1. 北京邮电大学北京市智能通信软件与多媒体重点实验室
  2. 南昌大学计算机系
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP311.13
- Published：2009
- 稿件说明：
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ZHU Tian1, BAI Shi-xue2, WANG Bai1, et al. Mining association rules in interval-based temporal sequences[J]. 2009, 30(8): 112-115.
DOI：

ZHU Tian1, BAI Shi-xue2, WANG Bai1, et al. Mining association rules in interval-based temporal sequences[J]. 2009, 30(8): 112-115. DOI：

摘要

提出了一个新的基于时间段的频繁闭模式的挖掘算法

采用时间段的概念

利用频繁闭模式的特点

生成相应的时序规则。算法通过使用闭模式的性质进行剪枝优化

不生成冗余的候选序列

降低了时序规则发现的时间与空间复杂度

提高了效率。

Abstract

A new algorithm was proposed to find association rules in interval-based sequences

which was based on the concept of interval time series and used the properties of frequent closed patterns. By the properties of frequent closed patterns

the algorithm can avoid generating the redundancy candidate sequences

thus decreases the time and space complexity and improves the efficiency of the algorithm.

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