公开(公告)号：WO2017156067A1

公开(公告)日：2017-09-14

申请号：PCT/US2017/021278

申请日：2017-03-08

Applicant: WAL-MART STORES, INC.

Inventor： HIGH, Donald R. ,  JONES, Matthew Allen ,  NATARAJAN, Chandrashekar ,  ATCHLEY, Michael Dean ,  MCHALE, Brian Gerard

IPC: G06Q30/00

Abstract: A budget-constrained, machine-learning system is described that creates a shopping (purchase) list and performs on-line ordering and delivery. It receives the shopper's past purchase receipts from a retail store, pharmacy and/or auto center. It may attach to a web server to acquire on-line browsing information. The system creates a Purchase List from acquired information. The system receives a budget and determines if all items on the Purchase List can be bought under the budget. If not, the items are given priority ratings. The system walks down the list to in decreasing priority rating order identifying items to purchase without exceeding the budget. The shopper may override the items identified to be purchased. Shopper override is monitored by a machine learning engine which adjusts the priority rating of the item or the period of replacement for the next shopping trip/session, allowing for more accurate results and flexibility.

Abstract translation: 描述了预算受限的机器学习系统，其创建购物（购买）列表并执行在线订购和递送。 它从零售店，药房和/或汽车中心收到购物者的过去购物收据。 它可以连接到Web服务器以获取在线浏览信息。 系统根据获取的信息创建采购清单。 系统收到预算并确定购买清单上的所有项目是否可以在预算下购买。 如果不是，这些项目被赋予优先评级。 系统在列表中逐步降低优先级评级顺序，以确定要购买的商品而不超出预算。 购物者可以覆盖识别出要购买的物品。 购物者覆盖由机器学习引擎进行监控，该引擎调整物品的优先级或下一次购物行程/会话的替换周期，从而获得更准确的结果和灵活性。