AI_deation: A Creative Knowledge Mining Method for Design Exploration


  • George Palamas Aalborg University Copenhagen, Copenhagen, Denmark
  • Alejandra Mesa Guerra Aalborg University Copenhagen, Copenhagen, Denmark
  • Liana-Dorina Møsbæk Aalborg University Copenhagen



graphic design, visualization, design exploration, machine learning, gradient-based analysis, design theory, ideation


Ideation is a core activity in the design process which begins with a design brief and results in a range of design concepts. However, due to its exploratory nature it is challenging to formalise computationally. Here, we report a creative knowledge mining method that combines design theory with a machine learning approach. This study begins by introducing a graphic design style classification model that acts as a model for the aesthetic evaluation of images. A Grad-CAM technique is used to visualise where our model is looking at in order to detect and interpret visual syntax, such as geometric influences and color gradients, to determine the most influential visual semiotics. Our comparative analysis on two Nordic design referents suggests that our approach can be efficiently used to support and motivate design exploration. Based on these findings, we discuss the prospects of machine vision aided design systems to envisage concepts and possible design paths, but also to support educational objectives.


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How to Cite

Palamas G, Guerra AM, Møsbæk L-D. AI_deation: A Creative Knowledge Mining Method for Design Exploration. EAI Endorsed Trans Creat Tech [Internet]. 2022 Nov. 23 [cited 2022 Dec. 3];9(3):e5. Available from: