公开(公告)号：US20230111978A1

公开(公告)日：2023-04-13

申请号：US17910756

申请日：2020-03-18

Applicant: GOOGLE LLC

Inventor： Andreas Veit ,  Kimberly Wilber

IPC: G06N3/08 ,  G06F16/903

Abstract: Techniques are disclosed that enable learning an embedding space using cross-examples, where a distance between a query and an electronic resource in the embedding space provides an indication of the relevance of the electronic resource to the query. Various implementations include learning the embedding space using cross-example Softmax techniques. Various implementations include leaning the embedding space using cross-example negative mining. Additional or alternative techniques are disclosed that enable determining an electronic resource for a query based on comparing a query vector (e.g., a embedding space representation of the query) with a set of pre-stored candidate electronic resource vectors (e.g., an embedding space representation of a set of candidate electronic resources).