Liu Shixia, Wang Xiting, Collins Christopher, Dou Wenwen, Ouyang Fangxin, El-Assady Mennatallah, Jiang Liu, Keim Daniel A
IEEE Trans Vis Comput Graph. 2019 Jul;25(7):2482-2504. doi: 10.1109/TVCG.2018.2834341. Epub 2018 May 8.
Visual text analytics has recently emerged as one of the most prominent topics in both academic research and the commercial world. To provide an overview of the relevant techniques and analysis tasks, as well as the relationships between them, we comprehensively analyzed 263 visualization papers and 4,346 mining papers published between 1992-2017 in two fields: visualization and text mining. From the analysis, we derived around 300 concepts (visualization techniques, mining techniques, and analysis tasks) and built a taxonomy for each type of concept. The co-occurrence relationships between the concepts were also extracted. Our research can be used as a stepping-stone for other researchers to 1) understand a common set of concepts used in this research topic; 2) facilitate the exploration of the relationships between visualization techniques, mining techniques, and analysis tasks; 3) understand the current practice in developing visual text analytics tools; 4) seek potential research opportunities by narrowing the gulf between visualization and mining techniques based on the analysis tasks; and 5) analyze other interdisciplinary research areas in a similar way. We have also contributed a web-based visualization tool for analyzing and understanding research trends and opportunities in visual text analytics.
视觉文本分析最近已成为学术研究和商业领域中最突出的主题之一。为了概述相关技术和分析任务，以及它们之间的关系，我们全面分析了1992年至2017年间在可视化和文本挖掘这两个领域发表的263篇可视化论文和4346篇挖掘论文。通过分析，我们得出了约300个概念（可视化技术、挖掘技术和分析任务），并为每种类型的概念构建了一个分类法。还提取了概念之间的共现关系。我们的研究可以作为其他研究人员的垫脚石，用于：1）理解本研究主题中使用的一组通用概念；2）促进对可视化技术、挖掘技术和分析任务之间关系的探索；3）了解当前开发视觉文本分析工具的实践；4）通过根据分析任务缩小可视化和挖掘技术之间的差距来寻找潜在的研究机会；5）以类似的方式分析其他跨学科研究领域。我们还提供了一个基于网络的可视化工具，用于分析和理解视觉文本分析中的研究趋势和机会。
