首页> 外文会议>IEEE International Conference on Data Mining >Mining Frequent Induced Subtree Patterns with Subtree-Constraint
【24h】

Mining Frequent Induced Subtree Patterns with Subtree-Constraint

机译:采矿频繁诱导具有子树约束的子树图案

获取原文

摘要

Mining frequent induced subtree patterns is very useful in domains such as XML databases, web log analyzing. However, because of the combinatorial explosion, mining all frequent subtree patterns becomes infeasible for a large and dense tree database. And too many frequent subtree patterns also confuse users. Usually only a small set of the mining results can arouse users' interests. In this paper, we propose a problem to discover frequent induced subtree patterns that are super trees of a given pattern tree specified by users, i.e. frequent induced subtree patterns with subtree-constraint. Most existing frequent subtree mining algorithms are based on right-most extension, which does not work well in the new problem. So free extension is presented to replace right-most extension in this paper. To avoid the duplicate pattern problem caused by free extension, we develop an efficient method that ensures no duplicate patterns in mining process or results. Then Subtree-Constraint Frequent Subtree Patterns Mining Algorithm, i.e. SCFS algorithm, is given. The experiment results also show that our algorithm achieves good performance.
机译:挖掘频繁诱导的子树模式在诸如XML数据库之类的域中非常有用,Web日志分析。然而,由于组合爆炸,挖掘所有频繁的子树图案对于大型和密集的树数据库而言是不可行的。太多频繁的子树模式也会混淆用户。通常只有一小部分挖掘结果可以引起用户的兴趣。在本文中,我们提出了一种问题,以发现频繁的诱导的子树图案,其是由用户指定的给定模式树的超级树的超级树,即使用子树限制频繁引起的子树模式。大多数现有的频繁的子树挖掘算法基于最右端的扩展,在新问题中不适用于良好的工作。因此,提出了自由扩展以替换本文的最佳扩展。为避免由自由扩展引起的重复模式问题,我们开发了一种有效的方法,可确保挖掘过程或结果中的重复模式。然后给出了子树约束频繁子树模式挖掘算法,即SCFS算法。实验结果还表明,我们的算法达到了良好的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号