摘要
在研究概念格和项集关系的基础上,将剪枝概念格模型引入数据库中项集的表示与挖掘,利用概念间的关系性质,在构造过程中及时、动态地剪枝,删除与项集求解无关的概念,不丢失信息的同时能有效压缩频繁项集的规模,实验证实了算法良好的性能。
The relationship between concept lattice and frequent itemsets is discussed,then the model of Pruned Concept Lattice （PCL） is introduced to represent itemsets in the database,and the scale of itemsets is compressed effficiently.The infrequent concepts is pruned timely and dynamically during the PCL＇s construction according to apriori property.The efficiency of the algorithm is shown in the experiments.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第22期176-178,共3页
Computer Engineering and Applications
基金
安徽省自然科学基金(the Natural Science Foundation of Anhui Province of China under Grant No.050420207)
国家自然科学基金(the National Natural Science Foundation of China under Grant No.050504F)。
关键词
数据挖掘
关联规则
项集
概念格
data mining
association rules
itemsets
concept lattice
