Adobe, Inc.

Kai Yeung Lau

Niranjan Shivanand Kumbi

Omar Rahman

Vaidyanathan Venkatraman

Atanu Ranjan Sinha

Shiv Kumar Saini

Ritwik Sinha

Gaurav Sinha

Ajay Awatramani

Rajan Madhavan

Akangsha Sunil Bedmutha

Badsah Mukherji

Amit Doda

In implementations of systems for predicting a terminal event, a computing device implements a termination system to receive input data defining a period of time and a maximum event threshold. This system uses a classification model to generate event scores for a plurality of entity devices. Each of the event scores indicates a probability of an event occurrence for a corresponding entity device within a period of time. The plurality of entity devices are segmented into a first segment and a second segment based on an event score threshold. Entity devices included in the first segment have event scores greater than the event score threshold and entity devices included in the second segment have event scores below the event score threshold. The termination system generates an indication of a probability that a number of event occurrences for the entity devices included in the second segment exceeds the maximum even threshold within the period of time.

Systems for predicting a terminal event

The present disclosure relates to systems, methods, and non-transitory computer readable media for generating a recommended target audience based on determining a predicted attendance utilizing a neural network approach. For example, the disclosed systems can utilize an approximate nearest neighbor algorithm to identify individuals that are within a similarity threshold of invitees for an event. In addition, the disclosed systems can implement an attendance prediction model to determine a probability of an invitee attending the event. The disclosed systems can further determine a predicted attendance for an event based on the individual probabilities. Based on identifying the similar individuals to, and the attendance probabilities for, the invitees, the disclosed systems can generate a recommended target audience to satisfy a target attendance for an event based on a predicted attendance for the event.

Generating a recommended target audience based on determining a predicted attendance utilizing a machine learning approach

Growing community of inventors

Seattle, WA, United States of America

Kai Yeung Lau