Robust test collections for retrieval evaluation
Ben Carterette · 2007
Low-cost methods for acquiring relevance judgments can be a boon to researchers who need to evaluate new retrieval tasks or topics but do not have the resources to make thousands of judgments. While these judgments are very useful for a one-time evaluation, it is not clear that they can be trusted when re-used to evaluate new systems. In this work, we formally define what it means for judgments to be reusable: the confidence in an evaluation of new systems can be accurately assessed from an existing set of relevance judgments. We then present a method for augmenting a set of relevance judgments with relevance estimates that require no additional assessor effort. Using this method practically guarantees reusability: with as few as five judgments per topic taken from only two systems, we can reliably evaluate a larger set of ten systems. Even the smallest sets of judgments can be useful for evaluation of new systems.