System and method for predicting clickthrough rates and relevance

Computer readable media comprising program code that when executed by a programmable processor causes execution of a method for predicting the relevance of a content item on the basis of one or more user clicks on the content item, the computer readable media comprising:

• program code for selecting one or more information need-content item pairs, a given information need-content item pair associated with click data and relevance data;
• program code for training a model to indicate a relationships between clicks and relevance on the basis of the click data and the relevance data for the one or more information need-content item pairs;
• program code for receiving an unlabeled information need-content item pair, the unlabeled information need-content item pair associated with click data but not relevance data;
• program code for applying the model to the unlabeled information need-content item pair to determine a relevance judgment;
• and
• program code for storing the relevance judgment.

A method for predicting a number of clicks for a content item on the basis of a relevance judgment for the content item, the method comprising:

• selecting one or more information need-content item pairs, a given information need-content item pair associated with click data and relevance data;
• training a model to indicate a relationships between clicks and relevance on the basis of the click data and the relevance data for the one or more information need-content item pairs;
• receiving an unlabeled information need-content item pair, the unlabeled information need-content item pair associated with relevance data but not click data;
• applying the model to the unlabeled information need-content item pair to determine the number of clicks for the content item;
• and
• storing a value that indicates the number of clicks.

Computer readable media comprising program code that when executed by a programmable processor causes execution of a method for predicting a number of clicks for a content item on the basis of a relevance judgment for the content item, the method comprising:

• program code for selecting one or more information need-content item pairs, a given information need-content item pair associated with click data and relevance data;
• program code for training a model to indicate a relationships between clicks and relevance on the basis of the click data and the relevance data for the one or more information need-content item pairs;
• program code for receiving an unlabeled information need-content item pair, the unlabeled information need-content item pair associated with relevance data but not click data;
• program code for applying the model to the unlabeled information need-content item pair to determine the number of clicks for the content item;
• and
• program code for storing a value that indicates the number of clicks.