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图学学报

图学学报

• 计算机图形学与虚拟现实 • 上一篇    下一篇

利用问题求解理论来研究交互式复杂信息的可视分析行为

  

  1. (1. 太原理工大学信息与计算机学院，山西晋中 030600；
    2. 山西传媒学院融媒技术学院，山西晋中 030600；
    3. 宾夕法尼亚州立大学信息科学与技术学院，美国宾夕法尼亚州 16802)
  • 出版日期:2020-06-30 发布日期:2020-08-18
  • 基金资助:
    国家自然科学基金项目(61572344)

Using problem-solving theories to investigate user behaviors in interactive visual analytics of complex information

  1. (1. College of Information and Computer Science, Taiyuan University of Technology, Jinzhong Shanxi 030600, China;
    2. College of Media Technology, Communication University of Shanxi, Jinzhong Shanxi 030600, China;
    3. College of Information Sciences and Technology, Pennsylvania State University, University Park 16802, USA)
  • Online:2020-06-30 Published:2020-08-18

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摘要： 面对大数据的挑战，力图将人的推理能力和计算系统的数据处理能力相结合的交
互式可视分析研究变得愈发重要。然而目前仍缺乏有效的认知理论来指导面向复杂信息的可视
分析系统的设计，诸如意义构建等现有的理论框架通常着眼于分析行为的外在特征，未能对此
类行为的内在认知机理进行深入研究。因此提出将问题求解作为一种理论框架来解释交互可视
分析行为的基本认知活动，并建议从非良构问题的角度来描述可视分析过程中用户所面临的主
要挑战，还从问题表征及问题求解策略等角度分析了可视分析系统对分析行为的影响。本研究
在理论上，将认知心理学领域的问题求解理论引入到交互可视分析行为的研究中，该方法对设
计面向复杂信息分析的其他类型交互系统也有启示作用；在实践层面上，从问题求解的支持角
度探索了可视分析系统的设计和评估问题。

关键词: 问题求解, 可视分析, 意义构建, 问题表征, 问题求解策略

Abstract: Recently, to address the challenges imposed by big data, research on interactive
visualization and visual analytics, which is aimed at combining human intelligence and machine
computational powers in data analysis, has become increasingly important. However, the design of
complex-information-oriented interactive visualization and visual analytics systems still lacks
effective cognitive foundations as a guidance. Existing frameworks or design guidelines, such as
sense-making, focus largely on the external characteristics of analytical activities and offer little
insight into fundamental cognition that underpins analytical behaviors. In this paper, we proposed a
theoretical framework based on problem-solving theories to help explain the essential cognitive
activities in interactive visual analytics, advocated an approach to understanding the visual analytics process as a process to solve ill-defined problems, and explored the impacts of problem
representations and problem-solving strategies on visual analytics behaviors. We see our contribution
as two-folded. Theoretically, we borrowed problem-solving theories from cognitive science to study
complex interactive activities in visual analytics, and this approach may offer insight into the design
of interactive systems involving complex information-analytical behaviors. Practically, we discussed
the design and evaluation of visual analytics tools from the perspective of supporting problem-solving.

Key words: problem-solving, visual analytics, sense-making, problem representation, problem-solving
strategy