Microsoft Technology Licensing, LLC

Myunghwan Kim

Shaunak Chatterjee

Mitul Tiwari

Souvik Ghosh

Yu Shi

Aastha Jain

Romer E Rosales-Delmoral

Brad Christopher Ciraulo

Haifeng Ji

Yafei Wang

Matthew Hsing Hung Walker

Shilpa Gupta

Yiou Xiao

Hema Raghavan

Florent Bekerman

Shruti Bhosale

Andrew P Hill

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

A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein are directed to Future Connection Engine that generates a select pairing of member accounts for a potential social network connection. The Future Connection Engine predicts, according to the prediction model, a first number of subsequent social network connections for a first member account in the select pairing that will occur after establishing the potential social network connection and a second number of subsequent social network connections for a second member account in the select pairing that will occur after establishing the potential social network connection. The Future Connection Engine generates connection recommendations for display to the select pairing based on whether the first and/or the second number of subsequent social network connections satisfies a threshold.

Future connection score of a new connection

The disclosed embodiments provide a system for facilitating interaction within a social network. During operation, the system obtains a set of attributes of a social network of a first member and a set of historic interactions in the social network. Next, the system analyzes the attributes and the historic interactions to predict an effect of a potential interaction between the first member and a second member of the social network on subsequent interactions in the social network. The system then uses the predicted effect to generate output for modulating the subsequent interactions in the social network.

Characterizing and managing social network interactions

This disclosure relates to systems and methods for expanding a social network. A method includes retrieving contact lists from a plurality of devices, generating a list of associations between identifiers in a first communication channel and identifiers in a second communication channel, removing, from the list of associations, one or more associations that include identifiers that do not represent contacts that are not members of the online social networking service, and transmitting an invitation to join the online social networking service to the second identifiers on the second communication channel for associations that remain in the list of associations.

Expanding a social network

Growing community of inventors

San Jose, CA, United States of America

Myunghwan Kim