1. A method for evaluating a search algorithm, comprising: defining a population of searches and database records from a search history database to provide a plurality of search/record pairs; applying a sampling method and direct sampling rates to each search/record pair in the population using a computing system, wherein search/record pairs having a higher variability relative to the population are assigned a relatively higher probability; randomly sampling a direct sample of search/record pairs with the computing system using the direct sampling rates to increase a likelihood of obtaining search/record pairs having the higher variability; running a search algorithm and measuring errors for the direct sample; and calculating an estimated error rate for the search algorithm using inverse probability weighting.