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Building And Applying A Human Cognition Model For Visual Analytics

机译:建立和应用人类认知模型进行视觉分析

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It is well known that visual analytics addresses the difficulty of evaluating and processing large quantities of information. Less often discussed are the increasingly complex analytic and reasoning processes that must be applied in order to accomplish that goal. Success of the visual analytics approach will require us to develop new visualization models that predict how computational processes might facilitate human insight and guide the flow of human reasoning. In this paper, we seek to advance visualization methods by proposing a framework for human 'higher cognition' that extends more familiar perceptual models. Based on this approach, we suggest guidelines for the development of visual interfaces that better integrate complementary capabilities of humans and computers. Although many of these recommenda-tions are novel, some can be found in existing visual analytics applications. In the latter case, much of the value of our contribution lies in the deeper ratio-nale that the model provides for those principles. Lastly, we assess these visual analytics guidelines through the evaluation of several visualization examples.
机译:众所周知,视觉分析解决了评估和处理大量信息的难题。讨论较少的是日益复杂的分析和推理过程,必须使用这些过程才能实现该目标。视觉分析方法的成功将要求我们开发新的可视化模型,以预测计算过程如何促进人类洞察力并指导人类推理流程。在本文中,我们试图通过提出人类“更高认知”的框架来扩展可视化方法,以扩展更熟悉的感知模型。基于此方法,我们建议开发可视界面的准则,以更好地集成人机互补能力。尽管这些建议中有许多是新颖的,但可以在现有的视觉分析应用程序中找到一些建议。在后一种情况下,我们所做贡献的大部分价值在于模型为这些原则提供的更深层次的比率。最后,我们通过评估几个可视化示例来评估这些可视化分析准则。

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