公开(公告)号：US20210004693A1

公开(公告)日：2021-01-07

申请号：US16551829

申请日：2019-08-27

Applicant: Google LLC

Inventor： Manas Rajendra Joglekar ,  Jay Adams ,  Sujeet Bansal

IPC: G06N5/04 ,  G06N20/00 ,  G06F16/955

Abstract: The present disclosure is directed to systems and methods that include a machine-learned label embedding model that generates feature-based label embeddings for labels in real-time, in furtherance, for example, of selection of labels relative to a particular entity. In particular, one example computing system includes both a machine-learned entity embedding model configured to receive and process entity feature data descriptive of an entity to generate an entity embedding for the entity and a machine-learned label embedding model configured to receive and process first label feature data associated with a first label to generate a first label embedding for the first label.

公开(公告)号：US11443202B2

公开(公告)日：2022-09-13

申请号：US16551829

申请日：2019-08-27

Applicant: Google LLC

Inventor： Manas Rajendra Joglekar ,  Jay Adams ,  Sujeet Bansal

IPC: G06N20/00 ,  G06N5/04 ,  G06F16/955 ,  G06N3/08

Abstract: The present disclosure is directed to systems and methods that include a machine-learned label embedding model that generates feature-based label embeddings for labels in real-time, in furtherance, for example, of selection of labels relative to a particular entity. In particular, one example computing system includes both a machine-learned entity embedding model configured to receive and process entity feature data descriptive of an entity to generate an entity embedding for the entity and a machine-learned label embedding model configured to receive and process first label feature data associated with a first label to generate a first label embedding for the first label.