Trees of classifiers for detecting email spam

US7930353B2 · kind B2 · utility

Assignee

• Microsoft Corporation · US

Inventors

• David M. Chickering · Bellevue, US
• Geoffrey J. Hulten · Bainbridge Island, US
• Robert L. Rounthwaite · Fall City, US
• Christopher A. Meek · Kirkland, US
• David E. Heckerman · Bellevue, US
• Joshua T. Goodman · Redmond, US

Key dates

• Filing date: Jul 29, 2005
• Grant date: Apr 19, 2011
• Expiry date: Sep 30, 2027

Classification

• Technology area (CPC H): Electricity
• CPC primary: H04L51/212
• WIPO field: Digital communication
• WIPO sector: Electrical engineering

Abstract

Decision trees populated with classifier models are leveraged to provide enhanced spam detection utilizing separate email classifiers for each feature of an email. This provides a higher probability of spam detection through tailoring of each classifier model to facilitate in more accurately determining spam on a feature-by-feature basis. Classifiers can be constructed based on linear models such as, for example, logistic-regression models and/or support vector machines (SVM) and the like. The classifiers can also be constructed based on decision trees. “Compound features” based on internal and/or external nodes of a decision tree can be utilized to provide linear classifier models as well. Smoothing of the spam detection results can be achieved by utilizing classifier models from other nodes within the decision tree if training data is sparse. This forms a base model for branches of a decision tree that may not have received substantial training data.