DocuCompass: Effective exploration of document landscapes

Florian Heimerl, M. John, Qi Han, Steffen Koch, T. Ertl
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引用次数: 37

Abstract

The creation of interactive visualization to analyze text documents has gained an impressive momentum in recent years. This is not surprising in the light of massive and still increasing amounts of available digitized texts. Websites, social media, news wire, and digital libraries are just few examples of the diverse text sources whose visual analysis and exploration offers new opportunities to effectively mine and manage the information and knowledge hidden within them. A popular visualization method for large text collections is to represent each document by a glyph in 2D space. These landscapes can be the result of optimizing pairwise distances in 2D to represent document similarities, or they are provided directly as meta data, such as geo-locations. For well-defined information needs, suitable interaction methods are available for these spatializations. However, free exploration and navigation on a level of abstraction between a labeled document spatialization and reading single documents is largely unsupported. As a result, vital foraging steps for task-tailored actions, such as selecting subgroups of documents for detailed inspection, or subsequent sense-making steps are hampered. To fill in this gap, we propose DocuCompass, a focus+context approach based on the lens metaphor. It comprises multiple methods to characterize local groups of documents, and to efficiently guide exploration based on users' requirements. DocuCompass thus allows for effective interactive exploration of document landscapes without disrupting the mental map of users by changing the layout itself. We discuss the suitability of multiple navigation and characterization methods for different spatializations and texts. Finally, we provide insights generated through user feedback and discuss the effectiveness of our approach.
DocuCompass:有效地探索文档景观
近年来,用于分析文本文档的交互式可视化的创建获得了令人印象深刻的势头。鉴于大量且仍在增加的可用数字化文本,这并不奇怪。网站、社交媒体、新闻通讯社和数字图书馆只是各种文本来源的几个例子,它们的可视化分析和探索为有效地挖掘和管理隐藏在其中的信息和知识提供了新的机会。对于大型文本集合,一种流行的可视化方法是在2D空间中用字形表示每个文档。这些景观可以是在2D中优化成对距离以表示文档相似性的结果,或者它们直接作为元数据提供,例如地理位置。对于定义良好的信息需求,可以为这些空间化提供合适的交互方法。然而,在标记文档空间化和阅读单个文档之间的抽象层次上的自由探索和导航在很大程度上是不受支持的。因此,针对任务定制的操作(例如选择文档子组以进行详细检查)或随后的意义构建步骤的重要查找步骤受到阻碍。为了填补这一空白,我们提出了doccompass,这是一种基于镜头隐喻的焦点+上下文方法。它包含多种方法来描述本地文档组,并根据用户需求有效地指导探索。因此,doccompass允许对文档景观进行有效的交互式探索,而不会因为改变布局本身而破坏用户的心理地图。我们讨论了多种导航和表征方法对不同空间化和文本的适用性。最后,我们提供了通过用户反馈产生的见解,并讨论了我们方法的有效性。
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