食品安全大数据可视化关联分析

陈谊; 孙梦; 武彩霞; 孙小然

doi:10.11959/j.issn.2096-0271.2021014

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食品安全大数据可视化关联分析

专题：大数据可视分析应用 | 更新时间：2024-06-03

- 食品安全大数据可视化关联分析
- Visual associations analysis of big data in food safety
- 大数据 2021年7卷第2期页码：2021014
- 作者机构：
- 作者简介：
  
  [ "陈谊（1963- ），女，博士，北京工商大学教授，食品安全大数据技术北京市重点实验室主任，中国图象图形学学会可视化与可视分析专业委员会副主任，中国计算机学会杰出会员。主要研究方向为可视化与可视分析、智能信息处理、食品安全大数据技术。2016年获得中国分析测试协会科学技术奖（CAIA奖）特等奖，2017年获得中国石油和化工科技进步奖二等奖。多次担任PacificVis、ChinaVis、ChinaVR等可视化学术会议程序委员会委员和审稿人。" ]
  [ "孙梦（1996- ），女，北京工商大学计算机学院硕士生，主要研究方向为可视化与可视分析、食品安全大数据技术。" ]
  [ "武彩霞（1998- ），女，北京工商大学计算机学院硕士生，主要研究方向为可视化与可视分析。" ]
  [ "孙小然（1997- ），女，北京工商大学计算机学院硕士生，主要研究方向为可视化与可视分析。" ]
- 基金信息：
  
  国家重点研发计划资助项目;The National Key Research and Development Program of China(2018YFC1603602);国家自然科学基金资助项目;The National Natural Science Foundation of China(61972010)
- DOI：10.11959/j.issn.2096-0271.2021014
  中图分类号： TP391.41
- 网络首发：2021-03，
  
  纸质出版：2021-03-15
- 稿件说明：
移动端阅览
陈谊, 孙梦, 武彩霞, 等. 食品安全大数据可视化关联分析[J]. 大数据, 2021,7(2):2021014.

Yi CHEN, Meng SUN, Caixia WU, et al. Visual associations analysis of big data in food safety[J]. Big data research, 2021, 7(2): 2021014.
陈谊, 孙梦, 武彩霞, 等. 食品安全大数据可视化关联分析[J]. 大数据, 2021,7(2):2021014. DOI： 10.11959/j.issn.2096-0271.2021014.

Yi CHEN, Meng SUN, Caixia WU, et al. Visual associations analysis of big data in food safety[J]. Big data research, 2021, 7(2): 2021014. DOI： 10.11959/j.issn.2096-0271.2021014.

摘要

随着检测技术的提高和互联网技术的广泛应用，食品安全数据的规模不断增大、类型不断增多，对数据分析技术提出了极大挑战。近年来出现的可视分析技术，通过提供图形交互界面，帮助领域人员深入理解数据并洞悉数据中的隐含规律，提高对食品安全风险的分析、发现、预警和溯源能力，为食品安全监测和管控提供了新手段。首先分析了食品安全数据的主要来源、特征和分析任务；然后提出了一种关联可视分析技术分类方法，从属性关联、实体关联、对比分析和时空分析4个方面阐述了近10年来的食品安全大数据可视化关联分析方法；最后提出了该领域存在的问题和挑战。

Abstract

With the improvement of detection technology and the wide application of Internet technology

the scale and types of food safety data continue to increase

which poses great challenges to data analysis technology.Visual analysis

which has emerged in recent years

can help domain experts gain a deeper understanding of the data and insight into the hidden patterns in the data by providing a graphical interactive interface.This in turn can improve the detection

analysis

early warning and traceability of food safety risks

providing new tools for food safety monitoring and surveillance.Firstly

the main sources

characteristics and analysis tasks of food safety big data were analyzed.Then

a classification method for visual associations analysis techniques was proposed

and the visual associations analysis methods for food safety big data in the past 10 years were described from four aspects: attribute correlation

entity associations

comparative analysis and spatio-temporal analysis.Finally

the problems and challenges in this field were presented.

关键词

Keywords

references

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