版本 1.0.9(11/27/2017):

添加了对 SketchUp 2017 的支持
修复了为 CSV 加载调整蛋糕宽度的错误

版本 1.0.8(2/10/2016):

添加了对 SketchUp 2016 的支持

版本 1.0.7(2015 年 1 月 29 日):

更正了圆圈周围单词按字母顺序排列的错误。
更正了在 Windows 上加载和转换 PDF 文件的错误

能够将信件、研究出版物、文学作品、剧本、副本和其他文本分组提炼成关键概念或词汇是很有价值的。还有很多方法可以处理和评估文本中的重要主题或思想。评估词频是一种通过信息图形(如词云、加权词表、数据云或标签云)获得流行的方法。然而,此类表示仅提供相对比较,通过字长传达,nd 仅比较一个文本的单词,而不是具体的字数,也不是涵盖多个文本的信息
作者:Ross T.
描述:我目前是威斯康星大学麦迪逊生活环境实验室的一名系统程序员。我们致力于推进虚拟现实、信息和科学可视化的科学发展,并将虚拟现实应用于家庭保健。\n\nBe
Version 1.0.9 (11/27/2017):

Added support for SketchUp 2017
Fixed a bug with adjusting cake width for CSV loads

Version 1.0.8 (2/10/2016):

Added support for SketchUp 2016

Version 1.0.7 (1/29/2015):

Corrected a bug with alphabetical ordering of words around the circles.
Corrected a bug with loading and converting PDF files on Windows

There is value in being able to distill correspondence, research publications, literary works, scripts, copy and other groupings of texts down to their key concepts or vocabulary. There are also many ways to approach and assess the important themes or ideas in a text. Evaluating word frequency is one method that has gained popularity through information graphics such as word clouds, weighted word list, data clouds or tag clouds. However, such representations offer only relative comparisons, conveyed through word size, and only comparison among words for one text, not specific numbers of word counts, nor information covering multiple text

单词蛋糕