公开(公告)号：US10678997B2

公开(公告)日：2020-06-09

申请号：US15825657

申请日：2017-11-29

Applicant: Microsoft Technology Licensing, LLC

Inventor： Karan Ashok Ahuja ,  Befekadu Ayenew Ejigou ,  Ningfeng Liang ,  Lokesh P. Bajaj ,  Wei Wang ,  Paul Fletcher ,  Wei Lu ,  Shaunak Chatterjee ,  Souvik Ghosh ,  Yang Li ,  Wei Deng ,  Qiang Wu

IPC: G06F17/00 ,  G06F40/174 ,  G06Q50/00 ,  G06N20/00 ,  H04L29/08

Abstract: In an example, first and second machine learned models corresponding to a particular context of a social networking service are obtained, the first machine learned model trained via a first machine learning algorithm to output an indication of importance of a social networking profile field to obtaining results in the particular context, and the second machine learned model trained via a second machine learning algorithm to output a propensity of the user to edit a social networking profile field if requested. One or more missing fields in a social networking profile for the user are identified. For each of one or more of the one or more missing fields, the field and an identification of the user are passed through the first and second machine learned models, and outputs of the first and second machine learned models are combined to identify one or more top missing profile fields.

公开(公告)号：US11979496B2

公开(公告)日：2024-05-07

申请号：US17644846

申请日：2021-12-17

Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor： Yongyu Chen ,  Wei Deng ,  Yizhong Wu ,  Minming Guo

IPC: H04L9/08

CPC classification number: H04L9/0891

Abstract: The present technology provides a method to regenerate secrets while a version of the system is operational, thus avoiding the loss of availability that would have resulted from a system shutdown. The technology described herein may work in a computing context that assigns a first secret in an active role and a second secret in the backup role. The technology described herein activates a second instance of the service with the key not being regenerated serving as the active key. The second instance is then moved to the production mode and the first version of the service is moved to the staging mode. A new secret is generated and then assigned to the first instance of the service while it runs in the staging mode. Once the secret rotation is complete, the primary service instance is then moved back to the production mode with the new key configuration.

公开(公告)号：US20190108209A1

公开(公告)日：2019-04-11

申请号：US15825657

申请日：2017-11-29

Applicant: Microsoft Technology Licensing, LLC

Inventor： Karan Ashok Ahuja ,  Befekadu Ayenew Ejigou ,  Ningfeng Liang ,  Lokesh P. Bajaj ,  Wei Wang ,  Paul Fletcher ,  Wei Lu ,  Shaunak Chatterjee ,  Souvik Ghosh ,  Yang Li ,  Wei Deng ,  Qiang Wu

IPC: G06F17/24 ,  G06F15/18 ,  G06Q50/00 ,  H04L29/08

Abstract: In an example, first and second machine learned models corresponding to a particular context of a social networking service are obtained, the first machine learned model trained via a first machine learning algorithm to output an indication of importance of a social networking profile field to obtaining results in the particular context, and the second machine learned model trained via a second machine learning algorithm to output a propensity of the user to edit a social networking profile field if requested. One or more missing fields in a social networking profile for the user are identified. For each of one or more of the one or more missing fields, the field and an identification of the user are passed through the first and second machine learned models, and outputs of the first and second machine learned models are combined to identify one or more top missing profile fields.