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Please enjoy three video recordings of real-time animation in the parlance of kaleidoscopic silk weaving, produced under the double category of interactive art and generative art, accompanied by relaxation music.
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•´¯`•.¸¸.•♪♫♪•.¸¸.•´¯`•.♥.•.¸¸.•´¯`•.💗.•´¯`•.¸¸.•.♥.•.¸¸.•´¯`•♪♫♪•.¸¸.•´¯`•
Please enjoy five images of interactive generative art of kaleidoscopic silk weaving. Click any image below to see gallery images displayed in a full-size carousel view and to comment on each image.
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SoundEagle 🦅ೋღஜஇ 
Abstract: As a lay user creates an art piece using an interactive generative art tool, what, if anything, do the choices they make tell us about them and their preferences? These preferences could be in the specific generative art form (e.g., color palettes, density of the piece, thickness or curvatures of any lines in the piece); predicting them could lead to a smarter interactive tool. Or they could be preferences in other walks of life (e.g., music, fashion, food, interior design, paintings) or attributes of the person (e.g., personality type, gender, artistic inclinations); predicting them could lead to improved personalized recommendations for products or experiences. To study this research question, we collect preferences from 311 subjects, both in a specific generative art form and in other walks of life. We analyze the preferences and train machine learning models to predict a subset of preferences from the remaining. We find that preferences in the generative art form we studied cannot predict preferences in other walks of life better than chance (and vice versa). However, preferences within the generative art form are reliably predictive of each other.
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