MACHINE LEARNED MODEL FOR ITEM RECOMMENDATIONS FOLLOWING FAILED ATTEMPTS

Fuente: WIPO "tomato"
A machine learned model for item recommendations following failed attempts to purchase those items. During a session, an online system receives a request to fulfill an order from a user device. The system receives a message indicating that an item from the order was not fulfilled. The system logs the item in connection with a profile of the user stored in a database of the online system. During a subsequent session with the user device, the system determines that the logged item is available for fulfillment. The system applies the model to output an intent score indicative of an intent of a user of the user device to acquire the logged item. The logged item is ranked based on the intent score, and a user interface is generated that includes a recommendation to acquire the logged item. The system causes the user device to display the generated user interface.