Invention Grant
- Patent Title: Combined wide and deep machine learning models for automated database element processing systems, methods and apparatuses
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Application No.: US17643881Application Date: 2021-12-13
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Publication No.: US12105765B2Publication Date: 2024-10-01
- Inventor: Bing Song , Jeffrey Michael Balbien , Hao Lu , Phillip Yang , Patrick Soon-Shiong
- Applicant: NantMedia Holdings, LLC
- Applicant Address: US CA El Segundo
- Assignee: NantMedia Holdings, LLC
- Current Assignee: NantMedia Holdings, LLC
- Current Assignee Address: US CA El Segundo
- Agency: Harness Dickey & Pierce P.L.C.
- Main IPC: G06F16/9535
- IPC: G06F16/9535 ; G06F40/284 ; G06F40/40 ; G06N3/045

Abstract:
A method of automated database element processing includes training a wide machine learning model with historical feature vector inputs to generate a wide ranked element output. The method includes training a deep machine learning model with the historical feature vector inputs to generate a deep ranked element output. The method includes generating a set of inputs specific to an individual entity, obtaining a set of current article database elements, and creating a feature vector input according to the set of inputs and the set of current article database elements. The method includes processing the feature vector input with the wide machine learning model to generate a wide ranked element list, processing the feature vector input with the deep machine learning model to generate a deep ranked element list, and merging database elements of the wide and deep ranked element lists to generate a ranked element recommendation output.
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