Interpreting Idea Maps: Pairwise Comparisons Reveal What Makes Ideas Novel
Interpreting Idea Maps: Pairwise Comparisons Reveal What Makes Ideas Novel
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DOI：
10.1115/1.4041856
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发表时间：
2018-12
影响因子：
3.3
通讯作者：
Faez Ahmed;S. Ramachandran;M. Fuge;Samuel T. Hunter;Scarlett R. Miller
中科院分区：
文献类型：
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作者：
Faez Ahmed;S. Ramachandran;M. Fuge;Samuel T. Hunter;Scarlett R. Miller
评估设计理念之间的相似性是许多设计评估的固有部分，以衡量新奇。在这样的评估任务中，人类擅长在不同的知识集之间建立心理联系，以根据其独特性对想法进行评分。然而，他们对新奇性的决定往往是主观的，难以解释。在本文中，我们展示了一种方法来揭示人类的判断设计理念相似性使用二维（2D）的想法地图。我们通过要求参与者进行简单的相似性比较来得出这些地图，这种形式是“想法A更类似于想法B还是想法C？”我们表明，这些地图提供了深入了解的想法之间的关系，并帮助理解设计领域。我们还建议，新的想法可以通过发现这些想法地图上的离群值来识别。为了证明我们的方法，我们进行实验评估两个彩色多边形（已知答案）和牛奶起泡剂草图（未知答案）。我们发现，想法地图揭示了参与者在判断想法相似性时所考虑的因素，并且该地图对噪声评级具有鲁棒性。我们还比较了参与者在白板上制作的物理地图与计算生成的想法地图，以比较人们如何看待设计项目的空间布置。该方法提供了一个新的研究方向，通过结合人类的判断和计算方法来获得地面真实的新奇度量。
Assessing similarity between design ideas is an inherent part of many design evaluations to measure novelty. In such evaluation tasks, humans excel at making mental connections among diverse knowledge sets to score ideas on their uniqueness. However, their decisions about novelty are often subjective and difficult to explain. In this paper, we demonstrate a way to uncover human judgment of design idea similarity using two-dimensional (2D) idea maps. We derive these maps by asking participants for simple similarity comparisons of the form “Is idea A more similar to idea B or to idea C?” We show that these maps give insight into the relationships between ideas and help understand the design domain. We also propose that novel ideas can be identified by finding outliers on these idea maps. To demonstrate our method, we conduct experimental evaluations on two datasets—colored polygons (known answer) and milk frother sketches (unknown answer). We show that idea maps shed light on factors considered by participants in judging idea similarity and the maps are robust to noisy ratings. We also compare physical maps made by participants on a white-board to their computationally generated idea maps to compare how people think about spatial arrangement of design items. This method provides a new direction of research into deriving ground truth novelty metrics by combining human judgments and computational methods.