摘要
提出了将本体规则和关联规则的一致性维护映射到样本空间中解决的策略。通过对基于样本空间的一致性规则模型的建立和证明得出基于规则的一致性判则,并在此基础上设计了基于本体的多维关联规则一致性维护算法MARCMAO,最终得到了基于本体的具有一致性的关联规则集。基于茶叶病虫害预测本体的实验结果表明,该策略具有较高的可行性和有效性。
This paper proposed a strategy that mapping rules of ontology and KDD association rules to the sample space to solve the consistency maintenance problem for rules.Obtained the consistency sentences based on rules through the establishment and proof of the consistency rule model based on sample space,and on the basis of which,designed MARCMAO,finally got the association rule set with consistency based on ontology.The experiment results of tea diseases and pests forecasting the ontology show that this strategy has a higher feasibility and validity.
出处
《计算机应用研究》
CSCD
北大核心
2010年第7期2583-2586,2601,共5页
Application Research of Computers
基金
国家"863"计划资助项目(2006AA10z249)
关键词
引言知识发现
多维关联规则
本体
规则一致性维护
KDD
multidimensional association rule
ontology
rules consistency maintenance
