Patent ID: 8250061

Claim:
A method for selecting a relevance function to determine a relevance of a query-content item pair, the method comprising: generating a training set comprising one or more content item-query pairs; determining, by a processor, a relevance function for each query-content item pair; modifying the relevance function using a loss function according to a relevance score adjustment function that accounts for query differentiation, wherein an output for the relevance score adjustment function receives the determined relevance function as input, wherein the query differentiation is a difference between a training relevance value and the output of the relevance score adjustment function, and wherein the loss function L for determining an optimal relevance function F is L ⁡ ( F , α , β ) = ∑ q = 1 Q ⁢ ∑ j = 1 n q ⁢ [ y qj - α q - β q ⁢ F ⁡ ( x qj ) ] 2 + λ α ⁢  α  p p + λ β ⁢  β  p p , wherein α=[α 1 , . . . , α Q ] and β=[αβ 1 , . . . , β Q ], Q being a total number of queries, and β α >0, λ β are regularization parameters, x qi is a feature vector with query q, y qj is the training relevance value of the query-content item pair, n q is a number of content items associated with query q, and ∥•∥ p is the p norm of a given vector; and selecting a relevance function trained with query differentiation that produces a smallest loss, wherein the relevance function trained with query differentiation is selected when the modified relevance function and the training relevance value converge.