摘要
目前扩充和丰富本体存在很大的局限性.对此,文中提出采用多维关联规则技术扩展本体规则方法.通过对本体规则提取,在本体指导下的一致性处理,规则映射的建立,以及对概念本体的重新识别和更新等技术和方法充实和扩展概念本体.茶病虫害预测本体的实验结果表明该方法易于实现且具有较高的可行性和有效性.
Currently, the extension and enrichment for ontology have some limitations. Therefore, an approach is presented to extend ontology rules with multi-dimensional association rule technology. The conception ontology is enriched and extended by ontology rules extraction, consistency treatment under guidance of the ontology, rules mapping establishment, and the re-identification and update for conception ontology. The experimental results of tea diseases and pests predicting ontology show that the proposed approach can be easily implemented and has good feasibility and validity.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2009年第5期756-762,共7页
Pattern Recognition and Artificial Intelligence
基金
国家863计划资助项目(No.2006AA10z249)
关键词
本体
知识发现(KDD)
多维关联规则
规则扩展
Ontology, Knowledge Discovery in Database (KDD), Muhidimensional Association Rule, Rule Extension