摘要
针对目前人们对于食品安全的要求,笔者提出了一种基于知识图谱的食品问题溯源系统设计方法。首先,利用Scrapy爬虫框架对中国食品安全网、食品检测报告等信息抓取与采集,其次经过处理得到标准数据并对食物实体及关系进行抽取,最后基于Neo4j数据库将知识存储并可视化。通过对于食品安全关系的可视化,详细描述各个实体间的语义关联和属性,从而帮助相关部门找到食品问题的源头。
In response to the current public demand for food safety, this paper proposes a design method based on knowledge graph for food problem traceability system. Firstly, the Scrapy framework is used to crawl and collect information from China’s Food Safety website and food inspection reports. Secondly, relevant data are obtained, and food entities and relationships are extracted.Finally, the knowledge is stored and visualized based on the Neo4j database. Through the visualization of food safety relationships, the semantic associations and attributes between the entities are described in detail, which helps the relevant authorities to find out the origin of food problems.
作者
周毓奇
曹蕊
ZHOU Yuqi;CAO Rui(College of Computer and Information Engineering,Hubei University,Wuhan Hubei 430062,China)
出处
《信息与电脑》
2022年第6期171-174,179,共5页
Information & Computer
关键词
食品安全
知识图谱
实体抽取
可视化
food safety
knowledge graph
entity extraction
visualization
