Hierarchical statistical model for behavior prediction and classification

Abstract

Technologies are generally provided far a hierarchical, feature teed statistical model that cm be used for personalized classification or predictions within a community of users. Personalization refers to learning about the habits and characteristics of individual users and adapting user experiences based on that learning. The model may be used in a communication application to predict user actions on incoming email messages and to help users triage email by making personalized suggestions based on the model predictions. A community of users associated together with the communication application may be incorporated together into a single model to enable for continuous fine-grain interaction between intelligence learned from the community of users as a whole and that learned from individual users. The single model may allow a seamless progression between predictions for a completely new user based on community observations and highly personalized predictions for a long-term user based on individual observations.