公开(公告)号：US12265980B2

公开(公告)日：2025-04-01

申请号：US18240798

申请日：2023-08-31

Applicant: Maplebear Inc.

Inventor： Shuo Feng ,  Chia-Eng Chang ,  Aoshi Li ,  Pak Hong Wong ,  Leo Kwan ,  Mengyu Zhang ,  Van Nguyen ,  Aman Jain ,  Ziwei Shi ,  Ajay Pankaj Sampat ,  Rucheng Xiao

IPC: G06Q30/0201

Abstract: An online system receives information describing an order placed by a user of the online system and a set of contextual features associated with servicing the order. The online system also retrieves a set of user features associated with the user. The online system accesses a machine learning model trained to predict a tip amount the user is likely to provide for servicing the order and applies the machine learning model to a set of inputs, in which the set of inputs includes the information describing the order, the set of user features, and the set of contextual features. The online system then determines a suggested tip amount for servicing the order based on the predicted tip amount.

公开(公告)号：US20250021772A1

公开(公告)日：2025-01-16

申请号：US18769970

申请日：2024-07-11

Applicant: Maplebear Inc.

Inventor： Pak Hong Wong ,  Shengwen Fang ,  Tahmid Shahriar ,  Zyshia Williams

IPC: G06F40/58 ,  G06F40/106 ,  G06F40/166 ,  G06F40/232

Abstract: An online system performs a message transformation task in conjunction with the model serving system or the interface system to transform a message input to a chat message. The online system receives the message input in a conversation between a picker and a customer. The online system may transform the message input to a text string that is properly formed and contextually appropriate, format the text string into a chat message, and send the chat message to a receiving party on behalf of the sending party.

公开(公告)号：US20250078105A1

公开(公告)日：2025-03-06

申请号：US18240798

申请日：2023-08-31

Applicant: Maplebear Inc.

Inventor： Shuo Feng ,  Chia-Eng Chang ,  Aoshi Li ,  Pak Hong Wong ,  Leo Kwan ,  Mengyu Zhang ,  Van Nguyen ,  Aman Jain ,  Ziwei Shi ,  Ajay Pankaj Sampat ,  Rucheng Xiao

IPC: G06Q30/0201

Abstract: An online system receives information describing an order placed by a user of the online system and a set of contextual features associated with servicing the order. The online system also retrieves a set of user features associated with the user. The online system accesses a machine learning model trained to predict a tip amount the user is likely to provide for servicing the order and applies the machine learning model to a set of inputs, in which the set of inputs includes the information describing the order, the set of user features, and the set of contextual features. The online system then determines a suggested tip amount for servicing the order based on the predicted tip amount.