Design Puzzibility: design idea exploration based on design puzzles with deep learning

Abstract: The exploration of design ideas is a puzzle-solving process. The design puzzle as a framework motivates practitioners to explore more meaningful, refined, and preferable designs. This research tackles the factors that combine human-computer interaction on visual and semantic entities as hints to support the puzzles of concept design. Finding perfect references to express a specific design idea can be time-consuming and challenging. Mood boards have been used to motivate designers to visualize their creative concepts and convey insights to teams. This research illustrates the design puzzle with the mood board approach to support the idea exploration of web information system design. Several technical aspects of the design puzzle are surveyed and leveraged to achieve supporting design idea exploration with deep learning. With our computer-aided framework, designers may select the best combinations of design insights to work on further. To summarize, designers can use semantic and visual content analysis for problem-solving and idea exploration. This approach enables them to refine hinted ideas more flexibly and effectively.

Keywords: Design process, Design puzzles, Ideation, Image features, Natural language processing

DOI: 10.54941/ahfe1004236

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