公开(公告)号：US20250086189A1

公开(公告)日：2025-03-13

申请号：US18367185

申请日：2023-09-12

Applicant: Maplebear Inc.

Inventor： Levi Boxell ,  Esther Vasiete Allas ,  Tejaswi Tenneti ,  Tilman Drerup ,  Yueyang Rao

IPC: G06F16/2457 ,  G06F16/248

Abstract: A computer system allowing users to search for items of interest provides a search query interface. The system receives characters of a search query in the search interface as the user enters the characters and interactively calculates, ranks, and displays a set of possible search query options from which the user can select. To rank the set of possible search query options, the system modifies rankings of candidate search queries based on factors associated with third parties. More specifically, contextual relevance scores are computed for the candidate search queries based on the context, such as a user to whom the search results are provided. These contextual relevance scores are in turn adjusted using factors associated with third parties, such as values calculated based on consideration offered by third parties. Users are shown the search query options, ranked in order of the adjusted relevance scores, as possible query selections.

公开(公告)号：US20240354556A1

公开(公告)日：2024-10-24

申请号：US18640231

申请日：2024-04-19

Applicant: Maplebear Inc.

Inventor： Yueyang Rao ,  Brian Lin ,  Angadh Singh ,  Sharath Rao Karikurve ,  Guanghua Shu

IPC: G06N3/0455 ,  G06Q30/0601

CPC classification number: G06N3/0455 ,  G06Q30/0631

Abstract: An online system generates session-based recommendations for a user accessing an application of the online system. The online system receives, from one or more client devices, a sequence of actions performed by a user during a session of an application of an online system. The online system generates a sequence of tokens from the sequence of actions by tokenizing an action to a token representing a respective item identifier. The online system applies a transformer-based machine-learned model to the sequence of tokens to generate predictions for a set of items. The online system selects a subset of items based on the generated predictions for the set of items. The online system generates one or more recommendations to the user from the selected subset of items and displays the recommendations to the user.