Adaptive Effort for Search Evaluation Metrics.

We explain a wide range of search evaluation metrics as the ratio of users’ gain to effort for interacting with a ranked list of results. According to this explanation, many existing metrics measure users’ effort as linear to the (expected) number of examined results. This implicitly assumes that users spend the same effort to examine different results. We adapt current metrics to account for different effort on relevant and non-relevant documents. Results show that such adaptive effort metrics better correlate with and predict user perceptions on search quality.