Brand Product Recognition Model of Small and Medium-Sized Enterprises Based on AI Algorithm

To overcome the issue of insufficient accuracy in product selection methods used by small and medium-sized enterprises, the behavior and evaluation process of enterprise consumers were investigated. Statistics were analyzed to determine the level of consumer identification with commodity products and their level of engagement. The NDSC method was then employed to cluster consumers, followed by the use of the TOP-10 method for neighbor matching. Consequently, a product list for enterprise consumers was generated based on these neighbor-matching relationships. The results demonstrated that the algorithm exhibited superior accuracy, recall, and F-value compared to collaborative filtering algorithms and fusion algorithms.