摘要
结合目前国内外有关食源性疾病安全预警系统研究成果的现状分析,从知识挖掘角度出发,基于食品供应链体系,利用知识挖掘、领域本体等智能信息处理技术,构建一个用于"未知"食源性疾病知识发现、共享和流通的"事前预警"系统。并研究了基于食源性疾病领域本体的层次聚类挖掘、关联规则挖掘和决策树分类挖掘等一系列语义挖掘算法,并通过实验验证了算法的有效性。
Starting with an analysis of the current research achievements and shortcomings of foodborne disease safety early warning sys-tem at home and abroad, from the perspective of knowledge mining, based on food supply chain system, using intelligent information pro-cessing technology such as knowledge mining and domain ontology, an＆quot;early-warning＆quot; system is built for the knowledge discovery, sha-ring and distribution of the＆quot;unknown＆quot; foodborne diseases. A series of semantic mining algorithms based on foodborne disease domian on-tology, such as hierarchical clustering, association rule, and decision tree classification, are studied, and the effectiveness of the algo-rithms is verified by experiment.
出处
《情报杂志》
CSSCI
北大核心
2014年第2期18-22,共5页
Journal of Intelligence
基金
国家自然科学基金资助项目“企业竞争情报智能分析模型与方法研究”(编号:71073121)
湖北工程学院校级项目“知识挖掘技术在食品安全控制中的应用研究”(编号:r2013017)
关键词
食源性疾病
安全预警系统
语义挖掘
领域本体
foodborne disease
safety warning system
semantic mining
domain ontology
