US 6,665,653 B1 · Noise reduction for a cluster-based approach for targeted item delivery with inventory management

Abstract

Reduction of noise within a cluster-based approach for item (such as ad) allocation, such as by using a linear program, is described. In one embodiment, probabilities are discretized into a predetermined number of groups, where the mean for the group that a particular probability has been discretized into is substituted for the particular probability when the items are being allocated. In another embodiment, the probabilities are decreased by a power function of the variances for them. In a third embodiment, allocation of items to clusters is not changed unless the sample sizes used to determine the corresponding probabilities for those ads is greater than a threshold. In a fourth embodiment, after allocation is performed a first time, a predetermined number of item are removed, and reallocation is performed.

Claims19

Dependent claims

A computer-implemented method comprising:

allocating each of a plurality of items to at least one of a plurality of clusters, based on a predetermined criterion accounting for at least a quota for each item and comprising at least maximizing an expression ∑ ij ⁢ BucketProb ⁡ ( p ij ) ⁢ x ij ,
where pij comprises a probability that a user in cluster j will actuate item i, BucketProb(pij) comprises a function that returns a probability associated with a group to which pij is assigned in a discretization, and xij comprises a total number of times item i is effected in cluster j;
selecting an item for a current cluster from items allocated to the current cluster;
and,
effecting the item.

2 more elements

Dependencies are inferred from the claim text.

Noise reduction for a cluster-based approach for targeted item delivery with inventory management

Life of this patent

Noise reduction for a cluster-based approach for targeted item delivery with inventory management

Life of this patent

Abstract

Claims19