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Stream/Area:
-
Subject:
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Paper ID:
10.55041/IJSREM44812
Volume:
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Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The integration of Artificial Intelligence (AI) into creative workflows is transforming web design by enabling more personalized and efficient experiences. This study explores the development of AI-driven recommendation systems that suggest icons, fonts, and images based on designers’ preferences, project needs, and current design trends. The proposed framework combines collaborative filtering, content-based analysis, and contextual modeling to adapt to changing user requirements while encouraging both familiarity and creative exploration. An experimental study with 127 professional web designers showed a 37% reduction in element selection time, a 28% improvement in design coherence, and 82% reported enhanced creativity. Evaluation metrics included adoption rates, workflow efficiency, and creative diversity. Results highlight how AI recommendation systems can act as creative collaborators—enhancing, not replacing, human input. This work advances the field of AI- assisted design by presenting a balanced, adaptive framework that supports creative autonomy in modern web design.
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Publication Date
4/17/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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