US 2018/0026926 A1 · Graymail Filtering-Based On User Preferences

Abstract

A graymail detection and filtering system predicts whether a user will consider an email to be graymail using a classifier model based on features extracted from the email. The email is labelled as graymail or non-graymail based on the prediction. User actions are tracked on the email to determine whether the user actually considered the email to be graymail or non-graymail and the classifier model is trained using machine learning techniques to improve the prediction, without requiring explicit user feedback on whether the user considered the email to be graymail or non-graymail.

Claims24

Dependent claims

A method of detecting graymail without explicit user feedback, comprising:

receiving a non-spam email for a user;
extracting features of the email;
passing the extracted features to a classifier model;
predicting with the classifier model whether the user would consider the email as graymail;
modifying the email by inserting tracking information before delivering the email to the user;
storing the inserted tracking information in a tracking database;
tracking user actions on the email without explicit user feedback using the inserted tracking information;
updating the tracking database upon detection of tracked user actions on the email;
determining whether the user considered the email as graymail responsive to the tracked user actions without explicit user feedback;
and
training the classifier model responsive to the tracked user actions.

8 more elements

A non-transitory computer readable medium, on which is stored software for detecting graymail without explicit user feedback, comprising instructions that when executed by a graymail detection system cause the graymail detection system to:

receive a non-spam email for a user;
extract features of the email;
predict with a classifier model based on the extracted features whether the user would consider the email as graymail;
modifying the email by inserting tracking information before delivering the email to the user;
storing the inserted tracking information in a tracking database;
track user actions on the email without explicit user feedback using the inserted tracking information;
updating the tracking database upon detection of tracked user actions on the email;
determine whether the user considered the email as graymail responsive to the tracked user actions without explicit user feedback;
and
train the classifier model responsive to the tracked user actions.

7 more elements

A system for detecting graymail without explicit user feedback, comprising:

a data analytics computer system, comprising:
a processing element;
and
a memory, coupled to the processing element, on which is stored software for predicting whether a user would consider an email graymail, comprising instructions that when executed cause the processing element of the data analytics computer system to:
receive a non-spam email for a user;
extract features of the email;
predict with a classifier model based on the extracted features whether the user would consider the email as graymail;
and
train the classifier model responsive to tracked user actions;
and
a tracking engine computer system, comprising:
a processing element;
a tracking database;
and
a memory coupled to the processing element, on which is stored software for tracking user actions on the email, comprising instructions that when executed cause the processing element of the tracking engine computer system to:
modify the email by inserting tracking information before delivering the email to the user;
storing the inserted tracking information in a tracking database;
track user actions on the email without explicit user feedback using the inserted tracking information;
update the tracking database upon detection of tracked user actions on the email;
determine whether the user considered the email as graymail responsive to the tracked user actions without explicit user feedback;
and
provide information regarding the determination to the data analytics computer system for training the classifier model.

19 more elements

Dependencies are inferred from the claim text.

Graymail Filtering-Based On User Preferences

Life of this patent

Graymail Filtering-Based On User Preferences

Life of this patent

Abstract

Claims24