Microsoft Technology Licensing, LLC

Weigsheng Li

Mainak Sen

Ravi Kiran Reddy Poluri

Sharada Shirish Acharya

Yi Luo

Christian Rudnick

Emails or other communications are labeled with a category label such as 'spam' or “good” without using confidential or Personally Identifiable Information (PII). The category label is based on features of the emails such as metadata that do not contain PII. Graphs of inferred relationships between email features and category labels are used to assign labels to emails and to features of the emails. The labeled emails are used as a training dataset for training a machine learning model (“MLM”). The MLM identifies unwanted emails such as spam, bulk email, phishing email, and emails that contain malware.

Privacy-preserving labeling and classification of email

Emails or other communications are labeled with a category label such as 'spam' or 'good' without using confidential or Personally Identifiable Information (PII). The category label is based on features of the emails such as metadata that do not contain PII. Graphs of inferred relationships between email features and category labels are used to assign labels to emails and to features of the emails. The labeled emails are used as a training dataset for training a machine learning model (&#x201c;MLM&#x201d;). The MLM model identifies unwanted emails such as spam, bulk email, phishing email, and emails that contain malware.

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Redmond, WA, United States of America

Weigsheng Li