18. The computer-readable medium of claim 16 , the program code to configure the one or more processors to use the one or more features extracted from the given URL and the usefulness prediction model to generate the usefulness prediction in connection with the given URL further comprising program code to cause the one or more processors to: generate a positive usefulness prediction value in connection with the given URL using the one or more features extracted from the given URL and the usefulness prediction model; generate a negative usefulness prediction value in connection with the given URL using the one or more features extracted from the given URL and the usefulness prediction model; and compare the positive usefulness prediction value with the negative usefulness prediction value to generate the usefulness prediction in connection with the given URL.
18. The computer-readable medium of claim 16 , the program code to configure the one or more processors to use the one or more features extracted from the given URL and the usefulness prediction model to generate the usefulness prediction in connection with the given URL further comprising program code to cause the one or more processors to: generate a positive usefulness prediction value in connection with the given URL using the one or more features extracted from the given URL and the usefulness prediction model; generate a negative usefulness prediction value in connection with the given URL using the one or more features extracted from the given URL and the usefulness prediction model; and compare the positive usefulness prediction value with the negative usefulness prediction value to generate the usefulness prediction in connection with the given URL. 23. The computer-readable medium of claim 18 , the program code to configure one or more processors to generate a positive usefulness prediction value further comprising program code to configure the one or more processors to: determine the positive usefulness prediction value using a product, P, of a feature vector that identifies the features extracted from the given URL and a weighting vector that includes a weighting for each of the features extracted from the given URL to generate the positive usefulness prediction value using a formula: 1/(1+e −P ).