详细信息
基于极坐标布局的农残检出倾向性可视分析
Rotational Layout Visualization Method for Orientation Analysis of Pesticide Residue Detection Data
文献类型:期刊文献
中文题名:基于极坐标布局的农残检出倾向性可视分析
英文题名:Rotational Layout Visualization Method for Orientation Analysis of Pesticide Residue Detection Data
作者:陈红倩[1];杨倩玉[1];李慧[2];陈谊[1]
第一作者:陈红倩
机构:[1]北京工商大学计算机与信息工程学院食品安全大数据技术北京市重点实验室,北京100048;[2]北京联合大学管理学院,北京100101
第一机构:北京工商大学计算机与信息工程学院食品安全大数据技术北京市重点实验室,北京100048
年份:2019
卷号:55
期号:9
起止页码:190-196
中文期刊名:计算机工程与应用
外文期刊名:Computer Engineering and Applications
收录:CSTPCD;;北大核心:【北大核心2017】;CSCD:【CSCD_E2019_2020】;
基金:国家自然科学基金(No.31701517);北京市社会科学基金(No.17GLC060);"十三五"时期北京市属高校高水平教师队伍建设支持计划-青年拔尖人才培育计划(No.CIT&TCD201704039);北京工商大学国家两科基金培育项目(No.LKJJ2017-20);北京工商大学科研创新服务能力建设项目(No.PXM2018_014213_000033)
语种:中文
中文关键词:农残检测数据;信息可视化;数据分析;倾向性分析;极坐标布局
外文关键词:pesticide residue detection data;information visualization;data analysis;orientation analysis;polar coordinates layout
摘要:针对食品安全领域中农残检测数据的快速可视分析需求,提出了一种基于极坐标的旋转布局可视化方法。该方法首先按照用户的分析需求将数据信息进行分类统计;然后将检出农药的数据统计结果映射为农药圆,将农产品的数据统计结果映射为农产品图元,采用基于极坐标的旋转布局方式,将农药圆布局于环形结构中,将农产品图元布局于环形结构内部。通过图元偏移、鱼眼放大、多尺度筛选、半透明图形、添加同径向方向的标签以及调节农产品图元半径的方法降低农产品图元的重叠问题。实验结果与领域专家评价结果显示,提出的方法能快速地可视化数据集中的高兴趣度信息,既突出了多种农产品检出农药的倾向性,又同时对多附加属性实现直观简洁的显示。
To analyze the propensity of pesticide residues detected data in the field of food safety, a fast visualization and analysis method based on polar coordinates layout is proposed. The method calculates the detection frequency for each pesticide. The pesticide circles are obtained according to statistical results. The position and properties are calculated based on the polar coordinates. The statistical results of agricultural products are mapped into agricultural products shapes. The agricultural products shapes are arranged to emphasize the propensity of its containing pesticide residue based on the polar coordinates. The overlaping problem of agricultural products shapes is reduced by means of shape shifting,fisheye interaction, multi-scale filtering, semi-transparenting and tips labeling. It is denoted by the experimental results and food safety experts that the method can highlight simply and intuitively the propensity of detected pesticides for various agricultural products. The additional attributes can display synchronously in the final visualization results.
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