Invention Grant
- Patent Title: Generating neighborhood convolutions within a large network
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Application No.: US17577187Application Date: 2022-01-17
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Publication No.: US11922308B2Publication Date: 2024-03-05
- Inventor: Jurij Leskovec , Chantat Eksombatchai , Kaifeng Chen , Ruining He , Rex Ying
- Applicant: Pinterest, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Pinterest, Inc.
- Current Assignee: Pinterest, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Athorus, PLLC
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06F9/38 ; G06F16/182 ; G06F16/22 ; G06F16/51 ; G06F16/901 ; G06F16/9035 ; G06F16/906 ; G06F16/9535 ; G06F16/9536 ; G06F18/211 ; G06F18/214 ; G06F18/2413 ; G06N3/04 ; G06N20/00 ; G06V30/196

Abstract:
Systems and methods for generating embeddings for nodes of a corpus graph are presented. More particularly, operations for generation of an aggregated embedding vector for a target node is efficiently divided among operations on a central processing unit and operations on a graphic processing unit. With regard to a target node within a corpus graph, processing by one or more central processing units (CPUs) is conducted to identify the target node's relevant neighborhood (of nodes) within the corpus graph. This information is prepared and passed to one or more graphic processing units (GPUs) that determines the aggregated embedding vector for the target node according to data of the relevant neighborhood of the target node.
Public/Granted literature
- US20220318307A1 Generating Neighborhood Convolutions Within a Large Network Public/Granted day:2022-10-06
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