Requirement Analysis and Augmented Reality Interface Design for Custom Wood Veneer Cabinet Visualization Based on BERTopic Modeling
Keywords:
Wood veneer furniture, Anisotropic texture perception, Augmented reality, BERTopic topic modeling, User mental model, Interaction design, Usability evaluationAbstract
Augmented reality (AR) interfaces for custom wood-veneered cabinets require accurate requirement elicitation that accounts for the anisotropic optical properties of natural veneer. However, existing approaches lack a systematic pipeline linking large-scale user feedback to interface specifications. This paper presents a data-driven requirement mining framework that couples BERTopic semantic topic modeling with user mental model construction and cross-validates the two through a Jaccard-based semantic mapping coefficient (SMC). Applying the framework to a corpus of 3163 multi-source semantic units, the pipeline consolidated 18 initial clusters into four core requirement themes through hierarchical merging (CV coherence improved from 0.421 to 0.573) and translated them into a three-tier priority specification (P0/P1/P2) via a Comprehensive Priority Index. A high-fidelity AR prototype incorporating physically based anisotropic veneer rendering was evaluated with 60 participants across four user groups. The prototype achieved a System Usability Scale score of 82.5 (SD = 4.4) with no significant inter-group differences (F(3, 56) = 1.24, p = 0.303), confirming that the requirement-driven design pipeline can yield robust cross-group usability.
