Abstract: A method of filtering and scoring a plurality of resources where each resource can be associated with a plurality of attribute values. For each resource at least a subset of the attribute values can be applied to an input layer of a multilevel classifier, such as a neural network. The multilevel classifier can be used to generate intra-level values for nodes in an intermediate layer of the multilevel classifier and output values for node at an output layer of the multilevel classifier. The output values and associated intra-level values can be used to determine a confidence indicator or qualification score for the resource. The confidence indicators or qualification scores for the resources can be compared to filter the resources.