Multi-tiered approach to e-mail prioritization

A computer system comprising a memory tangibly embodying a set of instructions for automating a prioritization of an incoming message, the instructions causing the computer system to comprise:

• a plurality of classifiers comprising:
• a global classifier that is created with training data;
• and
• a user-specific classifier that is dynamically updated based on a feedback instance;
• a topic-based user model comprising a plurality of topic models;
• a feature extraction module that infers a topic of the incoming message and computes a plurality of contextual features of the incoming message based on the inferred topic of the incoming message;
• and
• a classification module that assigns a weight to each contextual feature of the plurality of contextual features based on a dynamic combination of the global classifier and the user specific classifier, combines the assigned weight of each contextual feature, and determines a priority level of the incoming message.

A computer system for automating a prioritization of an incoming message, the computer system comprising:

• a plurality of classifiers comprising:
• a global classifier that is created with training data;
• and
• a user-specific classifier that is dynamically updated based on a feedback instance;
• a topic-based user model comprising a plurality of topic models;
• a feature extraction module that infers a topic of the incoming message and computes a plurality of contextual features of the incoming message based on the inferred topic of the incoming message;
• and
• a classification module that assigns a weight to a set of contextual features of the plurality of contextual features based on a dynamic combination of the global classifier and the user specific classifier, combines the assigned weight of the set of contextual features, and determines a priority level of the incoming message.

An apparatus, comprising:

• an input to receive an incoming message;
• at least one processor;
• and
• a memory tangibly embodying a set of instructions for automating a prioritization of the incoming message, the instructions causing the apparatus to comprise:
• a feature extraction module that infers a topic of the incoming message based on a topic-based user model, and computes a plurality of contextual features of the incoming message based on the inferred topic of the incoming message;
• and
• a classification module that assigns a weight to the plurality of contextual features based on a dynamic combination of a plurality of classifiers and dynamically determines a priority classification strategy for assigning a priority level to the incoming message based on a combination of the assigned weight of the contextual features.