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DocuCompass: Effective exploration of document landscapes

机译:DOCUCPMAMAS:对文档景观有效探索

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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.
机译:近年来建立互动可视化以分析文本文件的势头令人印象深刻。鉴于大量且仍然越来越多的可用数字化文本,这并不令人惊讶。网站,社交媒体,新闻电线和数字图书馆只是不同的文本来源的例子,其视觉分析和探索提供了有效地挖掘和管理隐藏在他们内部的信息和知识的新机会。用于大型文本集合的流行可视化方法是表示2D空间中的字形的每个文档。这些景观可以是优化2D中的成对距离以表示文档相似性的结果,或者它们被直接提供为元数据,例如地理位置。对于定义明确的信息需求,可用于这些空间化的合适的交互方法。但是,在标记文档时空化和阅读单个文件之间的抽象级别的免费探索和导航在很大程度上不受支持。因此,用于任务定制行动的重要觅食步骤,例如选择用于详细检查的文件子组,或者随后的感应步骤受到妨碍。为了填补这种差距,我们提出了基于镜头隐喻的重点+上下文方法。它包含多种方法来表征本地文档组,并根据用户的要求有效地指导探索。因此,DOCUCCOMAMAS允许通过改变布局本身来扰乱用户的有效互动探索。我们讨论了不同的空间化和文本的多个导航和表征方法的适用性。最后,我们提供通过用户反馈产生的见解,并讨论我们方法的有效性。

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