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动态数据库中的频繁子树挖掘算法

Mining Frequent Subtrees from Dynamic Database
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摘要 针对动态数据库随时间发生改变的特性,提出了一种新的在动态数据库中挖掘频繁子树的算法,引入树的转变概率、子树期望支持度和子树动态支持度等概念,提出了动态数据库中的支持度计算方法和子树搜索空间,从而解决了数据动态变化的频繁子树挖掘问题。随着子树搜索的进行,算法定义裁剪公式和混合数据结构,能有效地减少子树搜索空间和提高频繁子树的同构速度。实验结果表明,新算法有效可行,且具有较好的运行效率。 On account of dynamic database＇s characteristic which is changing over time,a new algorithm aiming to mine frequent subtree from dynamic database was proposed.It put forward the support algorithm and subtree-searching space involving some concepts such as tree change probability,subtree expectation support and subtree dynamic support.The problem of mining frequent subtree from dynamic database was investigated.With the process of the subtree-searching,algorithm definition pruning expressions and mix data structure could reduce subtree-searching space and improve frequent subtree isomorphism speed efficiently.The experimental result showed that the new algorithm is effective and workable and has a better operating efficiency.
作者 郭鑫 董坚峰 周清平
机构地区 吉首大学信息管理与工程学院 武汉大学信息资源研究中心
出处 《计算机科学》 CSCD 北大核心 2011年第5期138-141,共4页 Computer Science
基金 国家自然科学基金项目(70573082) 教育部重点研究基地重大项目(08JJD870225)资助
关键词 数据挖掘 有序树 频繁子树 支持度 动态数据库 Data mining Ordered tree Frequent subtree Support Dynamic database
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献11

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二级参考文献67

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计算机科学
2011年 第5期

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