Information Retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
An exploration of axiomatic approaches to information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
A geometric interpretation and analysis of R-precision
Proceedings of the 14th ACM international conference on Information and knowledge management
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Ranking robustness: a novel framework to predict query performance
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Performance prediction using spatial autocorrelation
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Learning in a pairwise term-term proximity framework for information retrieval
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Predicting Query Performance by Query-Drift Estimation
ICTIR '09 Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory
Score distribution models: assumptions, intuition, and robustness to score manipulation
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Properties of optimally weighted data fusion in CBMIR
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Standard deviation as a query hardness estimator
SPIRE'10 Proceedings of the 17th international conference on String processing and information retrieval
Modeling score distributions in information retrieval
Information Retrieval
Improved query performance prediction using standard deviation
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Query performance prediction for IR
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Predicting query performance for fusion-based retrieval
Proceedings of the 21st ACM international conference on Information and knowledge management
Back to the roots: a probabilistic framework for query-performance prediction
Proceedings of the 21st ACM international conference on Information and knowledge management
On the inference of average precision from score distributions
Proceedings of the 21st ACM international conference on Information and knowledge management
Query-performance prediction and cluster ranking: two sides of the same coin
Proceedings of the 21st ACM international conference on Information and knowledge management
A Standard Document Score for Information Retrieval
Proceedings of the 2013 Conference on the Theory of Information Retrieval
Document Score Distribution Models for Query Performance Inference and Prediction
ACM Transactions on Information Systems (TOIS)
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The task of predicting query performance has received much attention over the past decade. However, many of the frameworks and approaches to predicting query performance are more heuristic than not. In this paper, we develop a principled framework based on modelling the document score distribution to predict query performance directly. In particular, we (1) show how a standard performance measure (e.g. average precision) can be inferred from a document score distribution. We (2) develop techniques for query performance prediction (QPP) by automatically estimating the parameters of the document score distribution (i.e. mixture model) when relevance information is unknown. Therefore, the QPP approaches developed herein aim to estimate average precision directly. Finally, we (3) provide a detailed analysis of one of the QPP approaches that shows that only two parameters of the five-parameter mixture distribution are of practical importance.