Journal of Computer Applications ›› 2021, Vol. 41 ›› Issue (4): 1005-1011.DOI: 10.11772/j.issn.1001-9081.2020081311

Special Issue: CCF第35届中国计算机应用大会(CCF NCCA 2020)

• The 35 CCF National Conference of Computer Applications (CCF NCCA 2020) • Previous Articles     Next Articles

Construction and correlation analysis of national food safety standard graph

QIN Li1,2, HAO Zhigang1, LI Guoliang1,2   

  1. 1. College of Informatics, Huazhong Agricultural University, Wuhan Hubei 430070, China;
    2. Hubei Engineering Technology Research Center of Agricultural Big Data (Huazhong Agricultural University), Wuhan Hubei 430070, China
  • Received:2020-08-27 Revised:2020-11-21 Online:2021-04-10 Published:2020-12-17
  • Supported by:
    This work is partially supported by the National Key Research and Development Program of China (2018YFC1604005).


秦丽1,2, 郝志刚1, 李国亮1,2   

  1. 1. 华中农业大学 信息学院, 武汉 430070;
    2. 湖北省农业大数据工程技术研究中心(华中农业大学), 武汉 430070
  • 通讯作者: 李国亮
  • 作者简介:秦丽(1978—),女,湖北武汉人,讲师,博士,CCF会员,主要研究方向:知识图谱、不确定性人工智能;郝志刚(1997—),男,山西阳泉人,硕士研究生,主要研究方向:知识图谱、大数据;李国亮(1972—),男,陕西西安人,教授,博士,CCF高级会员,主要研究方向:生物信息学、数据挖掘。
  • 基金资助:

Abstract: National Food Safety Standards(NFSS) are not only the operation specifications of food producers, but also the law enforcement criteria of food safety supervision. However, there are various NFSSs with a wide range of contents and complicated inter-reference relationships. To systematically study the contents and structures of NFSSs, it is necessary to extract the knowledges and mine the reference relationships in NFSSs. First, the contents of the standard files and the reference relationship between the standard files were extracted as knowledge triplets through the Knowledge Graph(KG) technology, and the triplets were used to construct the NFSS knowledge graph. Then, this knowledge graph was linked to the food production process ontology which was made manually based on Hazard Analysis Critical Control Point(HACCP) standards, so that the food safety standards and the related food production processes can be referenced to each other. At the same time, the Louvain community discovery algorithm was used to analyze the standard reference network in the knowledge graph, and the standards with high citations as well as their types in NFSSs were obtained. Finally, a question answering system was built using gStore's Application Programming Interface(API) and Django, which realized the knowledge retrieval and reasoning based on natural language, and the high-impact NFSSs in the graph could be found under specified requirements.

Key words: National Food Safety Standard (NFSS), knowledge graph, food production process ontology, community discovery algorithm, question answering system

摘要: 国家食品安全标准(NFSS)既是食品生产者的操作规范,也是食品安全监督的执法准绳。然而,NFSS种类繁多,它们涉及内容广泛,且相互引用关系复杂。为了系统地研究NFSS的内容与结构,对NFSS进行了知识抽取与引用关系挖掘。首先,利用知识图谱(KG)技术提取了标准文件的内容与标准文件之间的引用关系,以这些提取出来的内容作为三元组来构建NFSS知识图谱。然后将这个知识图谱与人工构建的基于危害分析关键控制点(HACCP)标准的食品生产过程本体相关联,使食品安全标准与相关的食品生产过程可以建立联系。同时利用Louvain社区发现算法对图谱中的标准引用网络进行分析,发现了在NFSS中引用度较高的标准及其类型。最后,利用gStore的应用程序接口(API)和Django搭建了一个问答系统,实现了基于自然语言的知识检索与推理,可以在指定需求下查询图谱中影响力较高的NFSS。

关键词: 食品安全国家标准, 知识图谱, 食品生产过程本体, 社区发现算法, 问答系统

CLC Number: