Performance prediction using spatial autocorrelation
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Query performance prediction for information retrieval based on covering topic score
Journal of Computer Science and Technology
Navigating in the Dark: Modeling Uncertainty in Ad Hoc Retrieval Using Multiple Relevance Models
ICTIR '09 Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory
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
Predicting Neighbor Goodness in Collaborative Filtering
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
Standard deviation as a query hardness estimator
SPIRE'10 Proceedings of the 17th international conference on String processing and information retrieval
LambdaMerge: merging the results of query reformulations
Proceedings of the fourth ACM international conference on Web search and data mining
A performance prediction approach to enhance collaborative filtering performance
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Predicting Query Performance by Query-Drift Estimation
ACM Transactions on Information Systems (TOIS)
Learning from the past: answering new questions with past answers
Proceedings of the 21st international conference on World Wide Web
Query performance prediction based on ranking list dispersion
FDIA'09 Proceedings of the Third BCS-IRSG conference on Future Directions in Information Access
Query performance prediction for IR
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Predicting the performance of passage retrieval for question answering
Proceedings of the 21st ACM international conference on Information and knowledge management
Query-Performance Prediction Using Minimal Relevance Feedback
Proceedings of the 2013 Conference on the Theory of Information Retrieval
Increasing evaluation sensitivity to diversity
Information Retrieval
Document Score Distribution Models for Query Performance Inference and Prediction
ACM Transactions on Information Systems (TOIS)
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We introduce a statistical measure of the coherence of a list of documents called the clarity score. Starting with a document list ranked by the query-likelihood retrieval model, we demonstrate the score's relationship to query ambiguity with respect to the collection. We also show that the clarity score is correlated with the average precision of a query and lay the groundwork for useful predictions by discussing a method of setting decision thresholds automatically. We then show that passage-based clarity scores correlate with average-precision measures of ranked lists of passages, where a passage is judged relevant if it contains correct answer text, which extends the basic method to passage-based systems. Next, we introduce variants of document-based clarity scores to improve the robustness, applicability, and predictive ability of clarity scores. In particular, we introduce the ranked list clarity score that can be computed with only a ranked list of documents, and the weighted clarity score where query terms contribute more than other terms. Finally, we show an approach to predicting queries that perform poorly on query expansion that uses techniques expanding on the ideas presented earlier.