Invention Grant
- Patent Title: Method and system of utilizing unsupervised learning to improve text to content suggestions
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Application No.: US16490456Application Date: 2019-05-01
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Publication No.: US11429787B2Publication Date: 2022-08-30
- Inventor: Ji Li , Xingxing Zhang , Furu Wei , Ming Zhou , Amit Srivastava
- Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC
- Applicant Address: US WA Redmond
- Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee Address: US WA Redmond
- Agency: NovoTechIP International PLLC
- International Application: PCT/CN2019/085397 WO 20190501
- International Announcement: WO2020/220370 WO 20201105
- Main IPC: G06F40/274
- IPC: G06F40/274 ; G06N20/20 ; G06F40/40

Abstract:
Method and system for training a text-to-content suggestion ML model include accessing a dataset containing unlabeled training data collected from an application, the unlabeled training data being collected under user privacy constraints, applying an ML model to the dataset to generate a pretrained embedding, and applying a supervised ML model to a labeled dataset to train the text-to-content suggestion ML model utilized by the application by utilizing the pretrained embedding generated by the supervised ML model.
Public/Granted literature
- US20210334708A1 Method and System of Utilizing Unsupervised Learning to Improve Text to Content Suggestions Public/Granted day:2021-10-28
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