Predicting geographic location associated with network address

A decision tree is provided as a machine learning classifier to predict a user attribute, such as a geographical location of a user, based on a network address. More specifically, the decision tree is constructed via machine learning on a set of sample data that reflects a relationship between a net...

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Bibliographische Detailangaben
Hauptverfasser: Maynard-Zhang, Pedrito U, Lloyd, Daniel, Mason, Llewellyn J, Minter, Samuel A
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung:A decision tree is provided as a machine learning classifier to predict a user attribute, such as a geographical location of a user, based on a network address. More specifically, the decision tree is constructed via machine learning on a set of sample data that reflects a relationship between a network address and a user attribute of a "known user" whose profile information is recognizable. For a given network address, the decision tree can be used as a machine learning classifier to predict the most likely user attribute of a potential user. With the predicted attribute, a network service can target a group of potential users for various campaigns without recognizing the identities of the potential users.