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research-article

Interpreting Idea Maps: Pairwise comparisons reveal what makes ideas novel

[+] Author and Article Information
Faez Ahmed

Dept. of Mechanical Engineering, University of Maryland, College Park, Maryland 20742
faez00@umd.edu

Sharath Kumar Ramachandran

School of Engineering Design, Technology and Professional Programs, The Pennsylvania State University, University Park, PA
sharath@psu.edu

Mark Fuge

Dept. of Mechanical Engineering, University of Maryland, College Park, Maryland 20742
fuge@umd.edu

Samuel Hunter

Industrial and Organizational Psychology, The Pennsylvania State University, University Park, PA
sth11@psu.edu

Scarlett Miller

School of Engineering Design, Technology and Professional Programs, The Pennsylvania State University, University Park, PA
shm13@psu.edu

1Corresponding author.

ASME doi:10.1115/1.4041856 History: Received June 30, 2018; Revised October 19, 2018

Abstract

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 and scoring ideas on their uniqueness. However, their decisions on 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 idea maps. We derive these maps by asking humans 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 of colored polygons (known answer) and milk frother sketches (unknown answer). We show that these maps shed light on factors considered by raters in judging idea similarity. We also show robustness of idea maps to fewer ratings or noisy ratings. We compare idea maps generated using triplet comparisons to physical maps manually made by the human subjects. This method provides a new direction of research into deriving ground truth novelty metrics by combining human judgments and computational methods.

Copyright (c) 2018 by ASME
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