VarifocalReader — In-Depth Visual Analysis of Large Text Documents
VarifocalReader — In-Depth Visual Analysis of Large Text Documents
复制标题
VarifocalReader — 大型文本文档的深入可视化分析
DOI：
10.1109/tvcg.2014.2346677
复制
发表时间：
2014
影响因子：
5.2
通讯作者：
Thomas Ertl
中科院分区：
文献类型：
--
作者：
Steffen Koch;M. John;Michael Wörner;Andreas Müller;Thomas Ertl
交互式可视化为探索、分析和理解文本文档提供了有价值的支持。然而，某些任务需要由人类专家仔细阅读源文本来验证来自视觉抽象的见解。到目前为止，这个问题通常是通过提供概述-细节技术来解决的，这种技术用不同层次的抽象来呈现不同的视图。这通常会导致视觉连续性的问题。另一方面，焦点上下文技术成功地突出了大型文本文档中有趣的子部分，但通常不适合集成视觉抽象。对于VarifocalReader，我们提出了一种技术，通过结合这两种方法的特性来帮助解决这些方法的一些问题。特别是，我们的方法通过基于文档的固有结构同时提供不同细节的抽象表示和对文本本身的访问，简化了处理大型且可能复杂的文本文档的工作。此外，VarifocalReader支持通过高级导航概念进行文档内部探索，并简化可视化分析任务。该方法使用户能够应用机器学习技术和搜索机制，以及评估和适应这些技术。这有助于从文本中提取实体、概念和其他工件。结合主题性主题分割自动生成中间文本层次，用户可以检验假设或提出有趣的新研究问题。为了说明我们方法的优点，我们提供了文献研究中的用法示例。
Interactive visualization provides valuable support for exploring, analyzing, and understanding textual documents. Certain tasks, however, require that insights derived from visual abstractions are verified by a human expert perusing the source text. So far, this problem is typically solved by offering overview-detail techniques, which present different views with different levels of abstractions. This often leads to problems with visual continuity. Focus-context techniques, on the other hand, succeed in accentuating interesting subsections of large text documents but are normally not suited for integrating visual abstractions. With VarifocalReader we present a technique that helps to solve some of these approaches' problems by combining characteristics from both. In particular, our method simplifies working with large and potentially complex text documents by simultaneously offering abstract representations of varying detail, based on the inherent structure of the document, and access to the text itself. In addition, VarifocalReader supports intra-document exploration through advanced navigation concepts and facilitates visual analysis tasks. The approach enables users to apply machine learning techniques and search mechanisms as well as to assess and adapt these techniques. This helps to extract entities, concepts and other artifacts from texts. In combination with the automatic generation of intermediate text levels through topic segmentation for thematic orientation, users can test hypotheses or develop interesting new research questions. To illustrate the advantages of our approach, we provide usage examples from literature studies.