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A Graph-Based Visualization of Time-Series Information in Multiple Texts

机译:基于图形的多个文本中时间序列信息的可视化

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Newspapers and other media often describe particular topics over some periods by giving a series of texts that introduces new information and corrects previous information. By analyzing such texts, we can understand how a topic changed over time and how the media treated it. However, analyzing such texts manually is time-consuming. To solve this problem, we propose a method for visualizing texts that describe a topic changing over time. For this purpose, we first generate an event information graph from such texts by using an existing method. Then we transform it into two different graphs. The first graph shows changes in the topic that we obtain by separating the initial graph and comparing the resulting time-dependent graphs. The second graph depicts a summary of the topic that we obtain by extracting high-frequency words from the initial graph. The results of our experiment show that our method can visualize changes and important information described in the texts.
机译:报纸和其他媒体通常会在一段时间内通过提供一系列介绍新信息并更正先前信息的文字来描述特定主题。通过分析此类文本,我们可以了解主题随时间的变化以及媒体如何对待它。但是,手动分析此类文本非常耗时。为了解决此问题,我们提出了一种可视化描述主题随时间变化的文本的方法。为此,我们首先使用现有方法从此类文本生成事件信息图。然后我们将其转换为两个不同的图。第一张图显示了我们通过分离初始图并比较所得的时间相关图而获得的主题变化。第二张图描述了我们从初始图中提取高频单词所获得的主题的摘要。实验结果表明,我们的方法可以可视化文本中描述的变化和重要信息。

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