Microsoft Technology Licensing, LLC

Haowen Cao

John P Moore

Chencheng Wu

Ankit Gupta

Yang Chen

Souvik Ghosh

Jing Wang

Thomas Michael Lee

Xiaojing Chen

Haifeng Zhao

Jiashuo Wang

Steven Kaplan

Yi Qun Zhou

Yayuan Hu

Mira Thambireddy

Ibraheem Abdul Malik

Henry Heyburn Pistell

Keyi Yu

Techniques for a flexible data security and machine learning system for merging third-party data are provided. In one technique, the system receives a data set from a third-party entity and receives selection data that indicates that the third-party entity selected a set of data security policies that includes an encryption option and a data mixing option from among multiple data mixing options. In response to receiving the selection data, the system stores data that associates the set of data security policies with the data set, encrypts the data set according to the encryption option, and persistently stores the encrypted data set. Later, the system decrypts the encrypted data set in volatile memory, generates, based on the data mixing option, training data based on the decrypted version of the data set, trains a machine-learned model based on the training data, and stores the machine-learned model in association with the data set.

Flexible data security and machine learning system for merging third-party data

Techniques are provided for identifying and presenting contextual course recommendations. A browser extension analyzes text within web content that is being displayed on a computing device. The browser extension, as part of the analysis, identifies one or more keywords. The browser extension transmits the one or more keywords over a computer network to a remote computer system. For each keyword, the remote computer system identifies one or more courses and one or more relevance scores, each of which reflects a relevance measure between the keyword and a course of the one or more courses. The remote system transmits, to the browser extension, course identification data that identifies one or more particular courses. The browser extension causes the course identification data to be displayed on the computing device.

Network system for contextual course recommendation based on third-party content

Techniques for managing multiple computing systems are provided. A system comprises a content delivery system (CDS) and an entity identification system (EIS). The CDS causes a content item that is associated with a content delivery campaign to be delivered over a computer network to a computing device of a user. The CDS detects that the user performed an action relative to the content item and, in response, creates an action record that indicates a particular entity associated with the user and that indicates an account that is associated with the content item and causes the action record to be made available to the EIS. The EIS, based on the account indicated in the action record, identifies a particular account from among multiple accounts indicated in an account database and searches the particular account for an entity (if any) that matches the particular entity.

Signal generation for one computer system based on online activities of entities with respect to another computer system

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Haowen Cao