Techniques for Enhancing the Relevancy of Candidate Item Selections Presented at a Self-Checkout

Fuente: WIPO "tomato"
A picklist of candidate predicted items for a non-barcoded item being purchased at a self-checkout terminal is enhanced to include other candidate predicted items that are visually indistinguishable from the candidate predicted items. An organic produce item PLU is included in the picklist for each non-organic PLU in the picklist. The organic produce item PLUs are ordered adjacent to the corresponding non-organic item PLUs to improve the consumer browsing experience and increase the likelihood that organic item purchases are accurately captured. Consumer selections from the picklist are returned to a machine learning model as feedback data to enable continuous learning and improved model accuracy. Non-organic produce item PLUs are returned for selections of organic produce items, thereby resulting in improved confidence values for non-organic PLUs and increased prediction accuracy of the model, while still ensuring organic items are included in the picklist and without requiring lowering of a confidence threshold.