论文标题
人力计算数据科学民主化的合作
Human-Machine Collaboration for Democratizing Data Science
论文作者
论文摘要
每个人都想分析他们的数据，但是只有很少的数据科学专业知识。在这种观察的激励下，我们引入了一个新颖的框架和系统\ textsc {visualsynth}，以进行数据科学中的人机合作。 它希望通过允许用户与标准电子表格软件进行交互，以执行和自动化各种数据分析任务，从数据争吵，数据选择，群集，约束学习，预测性建模和自动完成等各种数据分析。 \ textsc {visualsysnth}依赖于提供彩色草图的用户，即电子表格的着色部分，用于部分指定数据科学任务，然后使用人工智能技术确定和执行这些任务。
Everybody wants to analyse their data, but only few posses the data science expertise to to this. Motivated by this observation we introduce a novel framework and system \textsc{VisualSynth} for human-machine collaboration in data science. It wants to democratize data science by allowing users to interact with standard spreadsheet software in order to perform and automate various data analysis tasks ranging from data wrangling, data selection, clustering, constraint learning, predictive modeling and auto-completion. \textsc{VisualSynth} relies on the user providing colored sketches, i.e., coloring parts of the spreadsheet, to partially specify data science tasks, which are then determined and executed using artificial intelligence techniques.
