On score distributions and relevance
ECIR'07 Proceedings of the 29th European conference on IR research
Extending average precision to graded relevance judgments
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Modeling score distributions in information retrieval
Information Retrieval
Measuring the ability of score distributions to model relevance
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
Investigating performance predictors using monte carlo simulation and score distribution models
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
On the inference of average precision from score distributions
Proceedings of the 21st ACM international conference on Information and knowledge management
Document Score Distribution Models for Query Performance Inference and Prediction
ACM Transactions on Information Systems (TOIS)
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In this paper, we aim to investigate the practical usefulness of the Recall-Fallout Convexity Hypothesis (RFCH) for a number of document score distribution (SD) models. We compare SD models that do not automatically adhere to the RFCH to modified versions of the same SD models that do adhere to the RFCH. We compare these models using the inference of average precision as a measure of utility. For the three models studied in this paper, we conclude that adhering to the RFCH is practically useful for the two-normal model, makes no difference for the two-gamma model, and degrades the performance of the two-lognormal model.