边缘捆绑技术在媒体分析结果可视化中的应用

W. Kienreich, C. Seifert
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引用次数: 18

摘要

消费者生成媒体和社交媒体的出现导致了媒体格局的不断扩张和多样化。媒体消费者经常发现自己为了满足个人信息需求而扮演媒体分析师的角色。我们建议采用知识可视化方法来支持复杂的媒体分析任务。在本文中,我们描述了一种使用节点链接图描述关键政治参与者之间语义关系的方法。我们的贡献包括一种力导向的边缘捆绑算法,该算法考虑了边缘的语义属性,算法的技术评估以及该方法在现实世界中的应用报告。由此产生的可视化促进了高级边缘模式的识别,这些模式表明了强烈的语义关系。它已由奥地利新闻社APA于2009年出版。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Application of Edge Bundling Techniques to the Visualization of Media Analysis Results
The advent of consumer-generated and social media has led to a continuous expansion and diversification of the media landscape. Media consumers frequently find themselves assuming the role of media analysts in order to satisfy personal information needs. We propose to employ Knowledge Visualization methods in support of complex media analysis tasks. In this paper, we describe an approach which depicts semantic relationships between key political actors using node-link diagrams. Our contribution comprises a force-directed edge bundling algorithm which accounts for semantic properties of edges, a technical evaluation of the algorithm and a report on a real-world application of the approach. The resulting visualization fosters the identification of high-level edge patterns which indicate strong semantic relationships. It has been published by the Austrian Press Agency APA in 2009.
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