Invention Grant
- Patent Title: Utilizing a graph neural network to generate visualization and attribute recommendations
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Application No.: US17654933Application Date: 2022-03-15
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Publication No.: US12093322B2Publication Date: 2024-09-17
- Inventor: Fayokemi Ojo , Ryan Rossi , Jane Hoffswell , Shunan Guo , Fan Du , Sungchul Kim , Chang Xiao , Eunyee Koh
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Keller Preece PLLC
- Main IPC: G06F16/904
- IPC: G06F16/904 ; G06N3/02

Abstract:
The present disclosure relates to systems, methods, and non-transitory computer readable media that utilize a graph neural network to generate data recommendations. The disclosed systems generate a digital graph representation comprising user nodes corresponding to users, data attribute nodes corresponding to data attributes, and edges reflecting historical interactions between the users and the data attributes; Moreover, the disclosed systems generate, utilizing a graph neural network, user embeddings for the user nodes and data attribute embeddings for the data attribute nodes from the digital graph representation. In addition, the disclosed systems generate, utilizing a graph neural network, user embeddings for the user nodes and data attribute embeddings for the data attribute nodes from the digital graph representation. Furthermore, the disclosed systems determine a data recommendation for a target user utilizing the data attribute embeddings and a target user embedding corresponding to the target user from the user embeddings.
Public/Granted literature
- US20230297625A1 UTILIZING A GRAPH NEURAL NETWORK TO GENERATE VISUALIZATION AND ATTRIBUTE RECOMMENDATIONS Public/Granted day:2023-09-21
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