Semantic-Driven Paradigm Shift in Campus Guide Design Leveraging the KE-AIGC Framework

Campus guide systems are crucial to university infrastructure, shaping the experiences of students, staff, and visitors. Current systems face critical challenges in three areas: capturing diverse user needs, translating emotional requirements into design elements, and integrating campus cultural identity. This study integrates Kansei Engineering (KE) and Generative Artificial Intelligence (AIGC) to propose a semantic-driven design method. Using Semantic Web and Natural Language Processing (NLP), it models demand semantics, extracts emotional semantics such as safety and belonging, and maps them to design semantics for AIGC to generate personalized guide solutions. The approach leverages data-driven emotional semantic analysis and generative models to improve path guidance precision and cultural representation. Results indicate significant improvements in user experience, pathfinding accuracy, and cultural communication, with higher user satisfaction. This method provides a new semantic-driven pathway for developing campus guide systems and development prospects.