Is this Real?: Generating Synthetic Data that Looks Real

M. Mannino, A. Abouzeid
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引用次数: 24

Abstract

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.
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这是真的吗?:生成看起来真实的合成数据
Synner是一种工具,它通过可视化和声明性地指定数据集的属性(如每个字段的统计分布、域及其与其他字段的关系),帮助用户生成看起来真实的合成数据。它通过更新生成的数据集的多个可视化,为每个用户交互提供即时反馈,甚至从一些用户示例和交互中提出数据生成规范。Synner直观地传达了统计数据生成的固有随机性。我们对Synner的评估表明,与流行的数据生成工具Mockaroo以及付费编写数据生成脚本的受雇开发人员相比,Synner在生成真实数据方面是有效的。
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