【24h】

Association Rule Mining Based on Concept Lattice

机译:基于概念格的关联规则挖掘

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

From the view of concept formation, the paper researched the theories and methods of data mining based on concept lattice theory. The process of knowledge discovery from database may be understood as the process of concept formation from database. The concept lattice theory provides such a formal tool to reflect the process of concept formation. Through this theory, the intension and extension can be formal expressed, the analysis objects can be converted to formal context, and from these formal contexts, the concepts in different hierarchies and their relations can be extracted, and the aim of data mining can be achieved. The algorithm of association rule mining includes two steps: the construction of concept lattice and the production of association rule. The paper produced a fast construction algorithm of incremental concept lattice based on indexed tree. The actual experiment results proved: the algorithm of this paper is faster and more efficient than the traditional association rule mining algorithms-Apriori algorithms, and the algorithm can automated delete the redundant rules, can carry the aim of association rule automated simplified.
机译:从概念形成的角度出发,研究了基于概念格理论的数据挖掘理论和方法。从数据库发现知识的过程可以理解为从数据库形成概念的过程。概念格理论提供了这样一种形式化的工具来反映概念形成的过程。通过这种理论,可以将内涵和扩展形式化表达,将分析对象转化为形式上下文,并从这些形式上下文中提取不同层次的概念及其关系,从而达到数据挖掘的目的。 。关联规则挖掘算法包括两个步骤:概念格的构造和关联规则的产生。本文提出了一种基于索引树的增量概念格快速构建算法。实际实验结果证明:本文算法比传统的关联规则挖掘算法-Apriori算法更快,效率更高,该算法可以自动删除冗余规则,可以达到简化关联规则的目的。

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