Clustering of banned food additives based on Word2vec

被引：0
|
作者：
Zhang, Yipeng [1 ]
Li, Xiaoli [1 ,2 ,3 ]
Wang, Kang [1 ]
Li, Yang [4 ]
机构：
[1] Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
[2] Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing 100124, Peoples R China
[3] Beijing Univ Technol, Engn Res Ctr Digital Community, Minist Educ, Beijing 100124, Peoples R China
[4] Commun Univ China CUC, Sch Int Studies, Beijing 100024, Peoples R China
来源：
PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020) | 2020年
基金：
中国国家自然科学基金;
关键词：
Food safety; Clustering; Word2vec;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
At present, food safety crimes frequently occur in China, which not only affects social stability and unity, but also affects the health and life safety of the general public. In this study, 3000 food safety crime judgments from the Wusong Cases Network are used as the data samples, and they are divided into corpus. Then the Word2vec algorithm is used to cluster the toxic and harmful additives in the corpus. The research shows that Word2vec algorithm can well complete the clustering of illegal additives in food safety crime cases, and found some unusual illegal additives which have a certain role in the future food safety crime.
引用
收藏
页码：3467 / 3471
页数：5
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