偏序结构环形图:一种大数据偏序结构可视化新方法

Partial ordered structure circular diagram: a new method for partial ordered structure visualization of big data

偏序结构图因其良好的知识可视化特性已在知识发现、数据挖掘等领域得以广泛应用。但在对大数据所形成的超大形式背景进行研究和分析时,偏序结构树形图存在的一些不足,使大数据可视化效果欠佳,不利于对大数据进行数据挖掘和知识发现。本文对偏序结构树形图进行改进,提出了可用于大数据分析的偏序结构环形图。对实例形式背景绘制出偏序结构环形图,并与其偏序结构树形图比较。实验结果表明,该方法清晰、直观,可视化效果较好,能更有效地呈现出大形式背景中的重要信息,可以应用在大数据的数据挖掘和知识发现中。

The partial ordered structure diagramhas been widely applied to knowledge discovery and data mining and many otherdomains due to its better visualization. However, the shortcomings of traditional partial ordered structure diagram has lead to indistinctvisualization results when researching and analyzing big data, which is not conducive to data mining and knowledge discovery.Through improving the traditional treemap, a newvisualizationmethod based on attribute partial ordered structure diagramis proposed, and the method can be used to analyze big data. Applying this method, a partial ordered structure diagramof a set ofbig data is mapped and compared with traditional tree map in this paper. The results showthat this approach is clear, intuitive, andvisualization effect is better, thereby the diagramshows more important information of the large amount of data.