Is this Real? Generating Synthetic Data that Looks Real

被引:31
作者
Mannino, Miro [1 ]
Abouzied, Azza [1 ]
机构
[1] New York Univ Abu Dhabi, Abu Dhabi, U Arab Emirates
来源
PROCEEDINGS OF THE 32ND ANNUAL ACM SYMPOSIUM ON USER INTERFACE SOFTWARE AND TECHNOLOGY (UIST 2019) | 2019年
关键词
Data Generation; Mixed-Initiative UI; Uncertainty Visualization;
D O I
10.1145/3332165.3347866
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Synner is a tool that helps users generate real-looking synthetic data by visually and declaratively specifying the properties of the dataset such as each field's statistical distribution, its domain, and its relationship to other fields. It provides instant feedback on every user interaction by updating multiple visualizations of the generated dataset and even suggests data generation specifications from a few user examples and interactions. Synner visually communicates the inherent randomness of statistical data generation. Our evaluation of Synner demonstrates its effectiveness at generating realistic data when compared with Mockaroo, a popular data generation tool, and with hired developers who coded data generation scripts for a fee.
引用
收藏
页码:549 / 561
页数:13
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