Abstract：The high quality data not only provides the most effective data sources but also ensures the credibility and availability of the mining knowledge for subsequent knowledge mining. In order to ensure the effectiveness and authenticity of the knowledge of data mining based on food safety events, this paper puts forward a kind of food safety event data cleaning process based on ontology construction technology, and evaluates the data cleaning. The data used for cleaning is produced by the food safety event of Jiuguijiu plasticizer. In the specific cleaning process, the cleaning ontology of food safety event by Protégé is constructed based on the seven-step method developed by the School of Medicine of Stanford University. A feasible operation scheme for exploring the cleaning of domain-specific data is provided, and some semantic knowledge to the cleaned data is added.
沈 思. 基于本体构建技术的食品安全事件数据清洗研究[J]. 电脑与电信, 2018, 1(11): 26-30.
Shen Si. Research on the Food Safety Event Data Cleaning Based on Ontology Construction Technology. Computer & Telecommunication, 2018, 1(11): 26-30.
2018, Vol. 1 
