  We propose an AI-assisted design concept exploration tool, the "Character
Space Construction" ("CSC"). Concept designers explore and articulate the
target product aesthetics and semantics in language, which is expressed using
"Design Concept Phrases" ("DCPs"), that is, compound adjective phrases, and
contrasting terms that convey what are not their target design concepts.
Designers often utilize this dichotomy technique to communicate the nature of
their aesthetic and semantic design concepts with stakeholders, especially in
an early design development phase. The CSC assists this designers' cognitive
activity by constructing a "Character Space" ("CS"), which is a semantic
quadrant system, in a structured manner. A CS created by designers with the
assistance of the CSC enables them to discern and explain their design concepts
in contrast with opposing terms. These terms in a CS are retrieved and combined
in the CSC by using a knowledge graph. The CSC presents terms and phrases as
lists of candidates to users from which users will choose in order to define
the target design concept, which is then visualized in a CS. The participants
in our experiment, who were in the "arts and design" profession, were given two
conditions under which to create DCPs and explain them. One group created and
explained the DCPs with the assistance of the proposed CSC, and the other did
the same task without this assistance, given the freedom to use any publicly
available web search tools instead. The result showed that the group assisted
by the CSC indicated their tasks were supported significantly better,
especially in exploration, as measured by the Creativity Support Index (CSI).
