论文标题
Deepvenn-使用深度学习框架TensorFlow.js创建区域占优势的Venn图的Web应用程序
DeepVenn -- a web application for the creation of area-proportional Venn diagrams using the deep learning framework Tensorflow.js
论文作者
论文摘要
动机：维恩图是可视化数据集之间的重叠和差异的最流行方法之一。当它是“区域占领”时，它特别有用；即，圆的大小和重叠与数据集的大小成正比。有一些可用的工具可以生成区域占优势的维恩图，但是其中大多数仅限于两个或三个圆圈，而其他工具则不可作为Web应用程序或仅接受数字，而不是ID列表作为输入。由于过时的算法来计算圆圈的最佳位置，因此某些现有解决方案的精度也有限。最新的机器学习和深度学习框架可以为此问题提供解决方案。结果：Deepvenn Web应用程序可以创建最多十组的区域占区域图。由于使用深度学习框架Tensorflow.js实现的算法，Deepvenn自动找到了最佳解决方案，其中圆之间的重叠与尽可能多的重叠大小相对应。唯一需要的输入是ID的两到十个列表。可选参数包括主标题，字幕，圆形标题和颜色的颜色和背景。用户可以选择在最终图中显示绝对数字或百分比。可以通过右键单击它并选择“保存为”来将图像保存为PNG文件。界面的右侧还显示了所有交叉点的数字和内容。可用性：DeepVenn可在https://www.deepvenn.com上找到。联系人：[email protected]
Motivation: The Venn diagram is one of the most popular methods to visualize the overlap and differences between data sets. It is especially useful when it is are 'area-proportional'; i.e. the sizes of the circles and the overlaps are proportional to the sizes of the data sets. There are some tools available that can generate area-proportional Venn Diagrams, but most of them are limited to two or three circles, and others are not available as a web application or accept only numbers and not lists of IDs as input. Some existing solutions also have limited accuracy because of outdated algorithms to calculate the optimal placement of the circles. The latest machine learning and deep learning frameworks can offer a solution to this problem. Results: The DeepVenn web application can create area-proportional Venn diagrams of up to ten sets. Because of an algorithm implemented with the deep learning framework Tensorflow.js, DeepVenn automatically finds the optimal solution in which the overlap between the circles corresponds to the sizes of the overlap as much as possible. The only required input is two to ten lists of IDs. Optional parameters include the main title, the subtitle, the set titles and colours of the circles and the background. The user can choose to display absolute numbers or percentages in the final diagram. The image can be saved as a PNG file by right-clicking on it and choosing "Save image as". The right side of the interface also shows the numbers and contents of all intersections. Availability: DeepVenn is available at https://www.deepvenn.com. Contact: [email protected]
