On the inference of average precision from score distributions

Modelling the document scores returned from an IR system for a given query using parameterised score distributions is an area of research that has become more popular in recent years. Score distribution (SD) models are useful for a number of IR tasks. These include data fusion, query performance prediction, determining thresholds in filtering applications, and tasks in the area of distributed retrieval. The inference of performance metrics, such as average precision, from these SD models is an important consideration. In this paper, we study the accuracy of a number of methods of inferring average precision from an SD model.