LabelTransfer - Integrating Static and Dynamic Label Representation for Focus+Context Text Exploration

2018 International Symposium on Big Data Visual and Immersive Analytics (BDVA)(2018)

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摘要
In recent years, interactive visualization to analyze text documents has gained an impressive momentum. This is not surprising considering the fast increase of electronically available textual documents of various kinds. These include, for example, patents, scholarly documents, social media messages, and many other sources that contain valuable knowledge and insights for many stakeholders. Interactive text visualization turned out to be an important means for exploring and gaining insights into complex and often large document collections. An established visualization strategy to represent such collections is using projection-based techniques that visualize documents as glyphs in a 2D view aiming to reflect the semantic similarity of documents by the proximity of their placement. Static labels have been suggested to characterize the overall topics contained in the projected data to improve the effectiveness of such visualization techniques. Other approaches employ magic lenses that enable users to explore the 2D spatialization freely on various granularity levels. In this work, we propose a visual exploration approach that combines cluster-based labeling of projected documents with an interaction concept for magic lens techniques. We offer a set of novel interactive features to support a smooth transition between static labels and the magic lens approach while exploiting the different levels of visual abstraction of both techniques without introducing additional clutter through overdraw. Finally, we provide insights gained from a preliminary user study and present the benefits of our approach.
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关键词
document collections,projection-based techniques,static labels,projected data,visualization techniques,visual exploration approach,cluster-based labeling,projected documents,interaction concept,magic lens techniques,novel interactive features,magic lens approach,visual abstraction,dynamic label representation,focus+context text exploration,interactive visualization,text documents,impressive momentum,fast increase,electronically available textual documents,social media messages,interactive text visualization
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