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

• Published in: International journal on semantic web and information systems Vol. 21; no. 1; pp. 1 - 27
• Main Authors: Chen, Xiaoqing, Wang, Juanfen, Zhuang, Yi
• Format: Journal Article
• Language: English
• Published: Hershey IGI Global 01.01.2025
• Subjects: Ambiguity; College campuses; Colleges & universities; Communication; Deep learning; Design; Designers; Emotions; Engineering; Environmental psychology; Generative artificial intelligence; Information systems; Infrastructure; Natural language processing; Navigation systems; Semantic web; Semantics; Translating; User experience; User needs; User satisfaction
• ISSN: 1552-6283; 1552-6291
• DOI: 10.4018/IJSWIS.368039

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.