| 摘要 |
A method and apparatus for finding predictive cross-category search queries for behavioral targeting in a networked online display advertising system. The methods include aggregating a training model dataset, the training model dataset comprising a history of clicks corresponding to historical advertisements. The training model dataset also contains plurality of targeting categories related to the history of clicks. Various techniques are disclosed for selecting a plurality of features from the training model dataset and calculating a click probability for a subject advertisement to be clicked by a user from a page, the calculating operations using features of the page that is to be presented to the user. Embodiments include mapping a particular query to one of the targeting categories and then presenting the subject advertisement selected on the basis of the value of the click probability. Normalization scales down the value of the click probabilities to filter out false positive categories.
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