Email threading based on machine learning
AssigneeMicrosoft Technology Licensing, LLC
InventorsCharles Yin-Che LEE, Victor POZNANSKI
Life of this patent
Estimating the term…
Abstract
Systems and methods are directed to email threading based on machine learning determined categories and features. A network system accesses a plurality of emails addressed to a user. The network system then classifies, using a machine learning model, each email into at least one of a plurality of categories. For a category of the plurality of categories, one or more feature values are extracted from each email in the category. Based on the category and the extracted feature values, the network system groups messages having a same feature value in the same category together into a single email thread. Information related to the single email thread is then presented at a client device of the user.
Claims20
A method comprising:
- training a preference model using training data obtained from feedback received from a user;
- accessing a plurality of emails addressed to a user;
- classifying each email into at least one of a plurality of categories;
- for a category of the plurality of categories, extracting one or more feature values from each email in the category;
- based on the category and the extracted feature values, grouping emails having a same feature value in the category together into a single email thread;
- based on the preference model, causing presentation of information related to the single email thread at a client device of the user;
- receiving additional feedback based on one or more interactions with the single email thread;
- and
- retraining the preference model based on the additional feedback.
A system comprising:
- one or more hardware processors;
- and
- a memory storing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising:
- training a preference model using training data obtained from feedback received from a user;
- accessing a plurality of emails addressed to a user;
- classifying each email into at least one of a plurality of categories;
- for a category of the plurality of categories, extracting one or more feature values from each email in the category;
- based on the category and the extracted feature values, grouping emails having a same feature value in the category together into a single email thread;
- based on the preference model, causing presentation of information related to the single email thread at a client device of the user;
- receiving additional feedback based on one or more interactions with the single email thread;
- and
- retraining the preference model based on the additional feedback.
A computer-storage medium comprising instructions which, when executed by one or more hardware processors of a machine, cause the machine to perform operations comprising:
- training a preference model using training data obtained from feedback received from a user;
- accessing a plurality of emails addressed to a user;
- classifying each email into at least one of a plurality of categories;
- for a category of the plurality of categories, extracting one or more feature values from each email in the category;
- based on the category and the extracted feature values, grouping emails having a same feature value in the category together into a single email thread;
- based on the preference model, causing presentation of information related to the single email thread at a client device of the user;
- receiving additional feedback based on one or more interactions with the single email thread;
- and
- retraining the preference model based on the additional feedback.
Dependencies are inferred from the claim text.