首页> 外国专利> FEEDBACK AND TRAINING FOR A MACHINE LEARNING ALGORITHM CONFIGURED TO DETERMINE CUSTOMER PURCHASES DURING A SHOPPING SESSION AT A PHYSICAL STORE

FEEDBACK AND TRAINING FOR A MACHINE LEARNING ALGORITHM CONFIGURED TO DETERMINE CUSTOMER PURCHASES DURING A SHOPPING SESSION AT A PHYSICAL STORE

机译:用于机器学习算法的反馈和培训,配置为在物理商店购物期间确定客户购物

摘要

An apparatus includes a processor. The processor receives an algorithmic shopping cart that includes a first set of items determined by an algorithm to have been selected by a person during a shopping session in a physical store, based on a set of inputs received from sensors located within the physical store. The processor also receives a virtual shopping cart that includes a second set of items. Video of the shopping session was captured by a set of cameras located in the physical store and depicts the person selecting the second set of items. The processor compares the algorithmic cart to the virtual cart and determines that a discrepancy exists between the algorithmic cart and the virtual cart. The processor determines a subset of the set of inputs associated with the discrepancy and attaches metadata explaining the discrepancy to the subset. The processor uses the subset to train the algorithm.
机译:装置包括处理器。处理器接收算法购物车,该算法购物车包括由在物理商店的购物会话期间由人类在物理存储中的购物会话期间选择的第一组项目,基于从位于物理存储器内的传感器接收的一组输入。处理器还接收包括第二组项目的虚拟购物车。购物会话的视频被一组位于物理商店的一组相机捕获,并描绘了选择第二组项目的人。处理器将算法推车与虚拟推车进行比较,并确定算法推车和虚拟推车之间存在差异。处理器确定与差异相关联的该组输入集的子集,并将元数据附加说明子集的差异。处理器使用子集训练算法。

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