Microsoft Technology Licensing, LLC

Matthew Hsing Hung Walker

Shaunak Chatterjee

Ajith Muralidharan

Shipeng Yu

Kinjal Basu

Yiping Yuan

Guanchao Wang

Myunghwan Kim

Sowmitra Thallapragada

Pratik Daga

Yiou Xiao

Yafei Wang

Manoj Sivakumar

Zhongen Tao

Adriel Fuad

Florent Bekerman

Yingkai Hu

Varun Bharill

Techniques for generating latent representations for entities based on a network graph are provided. In one technique, an artificial neural network is trained based on feature vectors of entities and feature vectors of neighbors of those entities. The neighbors are determined based on a graph of nodes representing the entities. Two nodes are connected if, for example, the corresponding entities are connected in an online network, one entity transmitted an online communication to the other entity, or one entity interacted with content associated with the other entity. Once trained, the artificial neural network is used to generate latent representations for entities represented by the graph. Latent representations may be used in multiple ways. For example, a similarity between two latent representations may be used to determine an order of candidate content items to present to an entity corresponding to one of the latent representations.

Latent feature extraction from a network graph

Technologies for determining whether to send notification messages, from different sources, to a target user are provided. The disclosed techniques include receiving a first notification event from a first notification service and receiving a second notification event from a second notification service. The first and second notification services are different services. Using a machine-learned model to assign a first score to the first notification event and a second score to the second notification event. Based on the first score, a determination is made to generate a first notification message for the first notification event. The first notification message is then sent to a target user. Based on the second score, a determination is made not to generate a second notification message for the second notification event.

Multi-objective, multi-input, efficient decoupling holistic platform for communication selection

A unified notification platform for offline creation and distribution of notification content from a variety of data sources is described. The notification platform provides data adaptors that are reusable for generating notifications of different types, specifically, for generating notifications of different types that have features that have meaning across different notification types such that these features can be used to generate comparable relevance scores with respect to candidate profiles. The relevance score calculated for a notification with respect to a member profile is used to determine whether the notification is to be presented to the member represented by the member profile.

Content generation and targeting

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Mountain View, CA, United States of America

Matthew Hsing Hung Walker