4.7 Article

Bridging Text Visualization and Mining: A Task-Driven Survey

期刊

出版社

IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2018.2834341

关键词

Visualization; visual text analytics; text mining

资金

  1. National Key RAMP
  2. D Program of China [SQ2018YFB100002]
  3. National Natural Science Foundation of China [61761136020, 61672308]
  4. Microsoft Research Asia
  5. Natural Sciences and Engineering Research Council of Canada (NSERC)
  6. German Research Foundation (DFG)
  7. Canada Research Chairs program

向作者/读者索取更多资源

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.

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