Patent ID: 7630917

Claim:
A computer-implemented method for learning to map mapping requested product attribute values onto product attribute values of available products, comprising the steps of: calculating via a processor a cost of a plurality of states of a state space, each of the plurality of states representing one or more available product attributes having zero or more decided attribute values, and calculating the cost is based, at least in part, on training data associated with previously requested and offered products and a summing of an average cost of deciding an attribute value for remaining undecided attributes; determining a next state of the state space such that one or more products are available and a sum of values, including a cost of the next state and a cost of a perturbation of one or more requested product attribute values to reach the next state is a minimum value, the cost of perturbation being determined according to a formula: c k i =−log(p(q i k )), where c k i is a cost of a k th perturbation of an i th product attribute value, q i k is the k th perturbation of the i th product attribute value, and p(q i k ) is a probability of selling the product having a value of an i th attribute perturbed according to q i k , the k th the perturbation the i th product attribute value; and mapping a value for a product attribute according to the minimum sum of values and product attribute values of available products.