Trees of classifiers for detecting email spam
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United States of America Patent
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Apr 19, 2011
Grant Date -
Feb 15, 2007
app pub date -
Jul 29, 2005
filing date -
Jul 29, 2005
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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.
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Patent Owner(s)
- MICROSOFT TECHNOLOGY LICENSING, LLC
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Inventor(s)
Inventor Name | Address | # of filed Patents | Total Citations |
---|---|---|---|
Chickering, David M | Bellevue, US | 84 | 4816 |
Goodman, Joshua T | Redmond, US | 100 | 8757 |
Heckerman, David E | Bellevue, US | 104 | 8029 |
Hulten, Geoffrey J | Lynnwood, US | 41 | 2494 |
Meek, Christopher A | Kirkland, US | 151 | 8300 |
Rounthwaite, Robert L | Fall City, US | 76 | 5357 |
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