Clustering of banned food additives based on Word2vec - 文章详情页

作者：

Zhang, Yipeng (Zhang, Yipeng.) | Li, Xiaoli (Li, Xiaoli.) (学者：李晓理) | Wang, Kang (Wang, Kang.) | Li, Yang (Li, Yang.)

收录：

EI Scopus

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.　©　2020　IEEE.

关键词：

Food safety Crime Food additives

作者机构：

[ 1 ] [Zhang, Yipeng]Beijing University of Technology, Faculty of Information Technology, 100124, China
[ 2 ] [Li, Xiaoli]Beijing University of Technology, Faculty of Information Technology, 100124, China
[ 3 ] [Li, Xiaoli]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing; 100124, China
[ 4 ] [Li, Xiaoli]Engineering Research Center of Digital Community, Ministry of Education, Beijing University of Technology, Beijing; 100124, China
[ 5 ] [Wang, Kang]Beijing University of Technology, Faculty of Information Technology, 100124, China
[ 6 ] [Li, Yang]Communication University of China (CUC), School of International Studies, Beijing; 100024, China

通讯作者信息：

李晓理
[li, xiaoli]engineering research center of digital community, ministry of education, beijing university of technology, beijing; 100124, china;;[li, xiaoli]beijing key laboratory of computational intelligence and intelligent system, beijing advanced innovation center for future internet technology, beijing university of technology, beijing; 100124, china;;[li, xiaoli]beijing university of technology, faculty of information technology, 100124, china

电子邮件地址：

lixiaolibjut@bjut.edu.cn

查看成果更多字段

成果类型
所属机构

所有年份指定年份从至