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针对专业分流数据的双层放射环矩阵可视化    

Double Sunburst Matrix Visualization to Overview Majors Distributary Data

文献类型:期刊文献

中文题名:针对专业分流数据的双层放射环矩阵可视化

英文题名:Double Sunburst Matrix Visualization to Overview Majors Distributary Data

作者:李慧[1];陈红倩[2];董爽[1];马丽仪[1]

第一作者:李慧

机构:[1]北京联合大学管理学院;[2]北京工商大学计算机与信息工程学院

第一机构:北京联合大学管理学院

年份:2017

卷号:0

期号:S1

起止页码:455-458

中文期刊名:计算机科学

外文期刊名:Computer Science

收录:CSTPCD;;北大核心:【北大核心2014】;CSCD:【CSCD_E2017_2018】;

基金:北京市自然基金资助项目:针对影视数据的个性化推荐关键技术研究(9164028)资助

语种:中文

中文关键词:数据可视化;专业分流数据;双层放射环;学生管理

外文关键词:Data visualization;;Majors distributary data;;Double sunburst;;Management of student

摘要:为表达并分析专业分流数据中的多属性流向特征分析,提出了一种双层放射环矩阵的可视化方法。该方法首先基于各属性条件对专业分流数据进行筛选和分类统计,然后将各统计结果指标映射为可视元素并展现到最终的可视化结果中。可视元素映射过程主要包含3部分:借鉴气泡图方法,将专业分流中的学生人数映射为气泡图形式;将饼图中的对比关系引入气泡图,将专业分流中各条件下的性别比例映射为放射环内层的饼图形式;借鉴Sunburst方法,将不同绩点条件下的学生数统计结果映射为放射环外层的区块。依托案例数据的实验结果与学生管理人员的评测结果表明,该可视化结果能对学生人数、性别、绩点等属性的流向特征进行直观表达,并能够对专业分流中的学生进行快速分类与细化,对专业建设与培养计划的制定起到良好的指导作用。
To show and analyze the feature of attribute flow in majors distributary data,a sunburst matrix visualization method was proposed in the paper.The data with various attributes are firstly selected and counted in the method.The statistical data are mapped to the visual elements of visualization results.The mapping procedure includes three parts.In the first part,the scattered bubble charts are introduced to express the whole statistical numbers of student with various source and destination.Secondly,contrast method of pie chart is introduced into bubbles to show its gender proportion.The pie chart is adopted as the inner layer of sunburst.Thirdly,the students' grade point attribute in each category are designed to display comparably in the outer layer of sunburst.The experimental results and the evaluation of the management staff denoted that the visualization results can be expressed directly to the flow characteristics such as the number of students,gender proportion,and grade point and so on.The detailed classification of students and professional construction and training are expected to achieve according to the visualization results.

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