Microsoft Technology Licensing, LLC

Peng Du

Shaunak Chatterjee

Rupesh Gupta

Shipeng Yu

Jinyun Yan

Anand Kishore

Mathew H Teoh

Embodiments include technologies to apply at least one machine learning model to features of a search query, features of a searcher user, features of a searchee content item, and features of a searchee user, produce a first outcome prediction that represents a probability of a first objective relating to engagement of the searcher user with a content item in an online system and a second outcome prediction that represents a probability of a second objective relating to engagement of the searchee user with the online system responsive to the engagement of the searcher user with the content item, apply a multi-objective optimization solver to the first objective, the second objective and an outcome prediction that is a combination of the first outcome prediction and the second outcome prediction, and generate a serving function for a search engine based on the first objective, the second objective, and the outcome prediction.

Results ranking with simultaneous searchee and searcher optimization

A method can include determining, based on learned parameter values, an intrinsic interest and an affinity for the user to be influenced to visit the website, determining, using the learned parameter values, intrinsic interest, and affinity for the user to be influenced to visit the website, a first probability indicating a likelihood that the user will, in response to viewing a badge notification, turn off notifications or delete an app and a second probability indicating a likelihood that the user will, in response to viewing the badge notification on the app, visit a website, in response to determining the second probability is greater than a threshold larger than the first probability, causing the app to include the badge notification when displayed on the user device.

Preventing notification blindness

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Houston, TX, United States of America

Peng Du