Multi-tiered approach to E-mail prioritization
First Claim
1. A method of automating incoming message prioritization, the method comprising:
- training a global classifier using message-level contextual features computed from a plurality of e-mail messages and a priority level assigned to each of the plurality of e-mail messages;
dynamically training a user-specific classifier using message-level contextual features computed from a plurality of feedback instances provided by a user regarding a priority level of previous incoming e-mail messages to the user;
dynamically assessing a message-specific quality of the user-specific classifier by computing a vector similarity or distance between the vector of message-level contextual features of an incoming message against the vectors of message-level contextual features of the plurality of feedback instances provided by the user;
selecting a priority classification strategy from a plurality of priority classification strategies based on the assessed quality of the user-specific classifier, the priority classification strategy using at least one of the global classifier and the user-specific classifier; and
classifying the incoming message based on the selected priority classification strategy.
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Abstract
A method of automating incoming message prioritization. The method including training a global classifier of a computer system using training data. Dynamically training a user-specific classifier of the computer system based on a plurality of feedback instances. Inferring a topic of the incoming message received by the computer system based on a topic-based user model. Computing a plurality of contextual features of the incoming message. Determining a priority classification strategy for assigning a priority level to the incoming message based on the computed contextual features of the incoming message and a weighted combination of the global classifier and the user specific classifier. Classifying the incoming message based on the priority classification strategy.
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Citations
14 Claims
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1. A method of automating incoming message prioritization, the method comprising:
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training a global classifier using message-level contextual features computed from a plurality of e-mail messages and a priority level assigned to each of the plurality of e-mail messages; dynamically training a user-specific classifier using message-level contextual features computed from a plurality of feedback instances provided by a user regarding a priority level of previous incoming e-mail messages to the user; dynamically assessing a message-specific quality of the user-specific classifier by computing a vector similarity or distance between the vector of message-level contextual features of an incoming message against the vectors of message-level contextual features of the plurality of feedback instances provided by the user; selecting a priority classification strategy from a plurality of priority classification strategies based on the assessed quality of the user-specific classifier, the priority classification strategy using at least one of the global classifier and the user-specific classifier; and classifying the incoming message based on the selected priority classification strategy. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method of automating a prioritization of an incoming message, the method comprising:
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creating a plurality of topic models for a user, each topic model to encode an interaction history that the user has with one of the user'"'"'s e-mail contacts, and relationship data with the user and one of the user'"'"'s e-mail contacts; computing a plurality of message-level contextual features of a plurality of e-mail messages received by the user, based on a content of the messages and the interaction history, the topic models, and the relationship data; training a global classifier using the plurality of message-level contextual features computed from the plurality of e-mail messages and a priority level assigned to each of the plurality of e-mail messages; dynamically training a user-specific classifier with a plurality of feedback instances provided by a user regarding a priority level of previous incoming e-mail messages to the user; dynamically assessing a message-specific quality of the user-specific classifier by comparing the vector of the message-level contextual features of an incoming message against the vectors of the message-level contextual features of the plurality of feedback instances provided by the user; selecting a priority classification strategy from a plurality of priority classification strategies based on the assessed quality of the user-specific classifier, the priority classification strategy using at least one of the global classifier and the user-specific classifier; and classifying the incoming message based on the selected priority classification strategy.
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13. A non-transitory tangible computer-readable medium embodying a program of machine-readable instructions executable by a digital processing apparatus to perform an instruction control method of automating a prioritization of an incoming message, the instruction control method comprising:
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training a global classifier using message-level contextual features computed from a plurality of e-mail messages and a priority level assigned to each of the plurality of e-mail messages; dynamically training a user-specific classifier using message-level contextual features computed from a plurality of feedback instances provided by a user regarding a priority level of previous incoming e-mail messages to the user; dynamically assessing a message-specific quality of the user-specific classifier by computing a vector similarity or distance between the vector of message-level contextual features of an incoming message against the vectors of message-level contextual features of the plurality of feedback instances provided by the user; selecting a priority classification strategy from a plurality of priority classification strategies based on the assessed quality of the user-specific classifier, the priority classification strategy using at least one of the global classifier and the user-specific classifier; and classifying the incoming message based on the selected priority classification strategy. - View Dependent Claims (14)
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Specification