D-Graph: AI-Assisted Design Concept Exploration Graph
Shin Sano, Seiji Yamada

TL;DR
D-Graph is an AI-powered tool that helps automotive designers generate unique, aesthetically meaningful two-adjective phrases by visualizing and filtering words based on frequency and similarity, aiding creative concept exploration.
Contribution
The paper introduces D-Graph, a novel AI-assisted visualization and retrieval tool that supports designers in creating original design-concept phrases using computational linguistic principles.
Findings
Participants using D-Graph showed a positive, but not significant, improvement in self-evaluated phrase quality.
Expert evaluations did not significantly differ between D-Graph and baseline.
A significant negative correlation was found between cosine similarity of words and expert ratings.
Abstract
We present an AI-assisted search tool, the "Design Concept Exploration Graph" ("D-Graph"). It assists automotive designers in creating an original design-concept phrase, that is, a combination of two adjectives that conveys product aesthetics. D-Graph retrieves adjectives from a ConceptNet knowledge graph as nodes and visualizes them in a dynamically scalable 3D graph as users explore words. The retrieval algorithm helps in finding unique words by ruling out overused words on the basis of word frequency from a large text corpus and words that are too similar between the two in a combination using the cosine similarity from ConceptNet Numberbatch word embeddings. Our experiment with participants in the automotive design field that used both the proposed D-Graph and a baseline tool for design-concept-phrase creation tasks suggested a positive difference in participants' self-evaluation on…
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Taxonomy
TopicsMachine Learning in Materials Science · Topic Modeling · Design Education and Practice
