A visualization recommendation approach based on machine learning
文献类型：会议论文
| 作者 | Wei SC(魏世超)2,3,4,5; Li X(李歆)2,3,5 ; Song PY(宋沛荫)1,2,3,4; Zhou XF(周晓锋)2,3,5; Zhang YC(张宜弛)2,3,5; Li S(李帅)2,3,4,5
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| 出版日期 | 2020 |
| 会议日期 | June 19-21, 2020 |
| 会议地点 | Shanghai, China |
| 关键词 | visualization recommendation machine Learning classification model |
| 页码 | 6-12 |
| 英文摘要 | As an important means of data analysis, data visualization is used by more and more people. For most people who don't have visualization technology expertise, data visualization has some Visualization recommendation aims to lower the barrier to exploring basic visualizations by automatically generating results for analysts to search and select.This paper proposes a visual recommendation method based on machine learning, which can learn the most meaningful visualization results from many visualization practice datasets and mark them.Firstly, 22 data features and corresponding meaningful visualization types are extracted from 30 real visualization datasets. Then, binary classifiers are used to train the classification model, from which we can learn meaningful visualization and use crowdsourced testsets to test the accuracy.Finally, the results of multiple classifiers are fused to vote for multiple meaningful charts in the datasets.Experiments show that this method can effectively learn the meaningful visualization types in datasets, mark and recommend them to users. |
| 源文献作者 | Bauman Moscow State Technical University ; Shanghai Maritime University ; Tokyo University of Science ; University of Houston-Downtown |
| 产权排序 | 1 |
| 会议录 | WCSE 2020: 2020 10th International Workshop on Computer Science and Engineering
 |
| 会议录出版者 | International Workshop on Computer Science and Engineering (WCSE) |
| 语种 | 英语 |
| ISBN号 | 978-981-14-4787-7 |
| 源URL | [http://ir.sia.cn/handle/173321/27733]  |
| 专题 | 沈阳自动化研究所_数字工厂研究室 |
| 通讯作者 | Zhou XF(周晓锋) |
| 作者单位 | 1.Shenyang University of Technology, China 2.Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang 110016, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 4.University of Chinese Academy of Sciences, Beijing 100049, China 5.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Wei SC,Li X,Song PY,et al. A visualization recommendation approach based on machine learning[C]. 见:. Shanghai, China. June 19-21, 2020. |
入库方式： OAI收割
来源：沈阳自动化研究所
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