The effect multiple query representations on information retrieval system performance
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Improving automatic query expansion
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Document language models, query models, and risk minimization for information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Language Modeling for Information Retrieval
Language Modeling for Information Retrieval
A survey on the use of relevance feedback for information access systems
The Knowledge Engineering Review
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Regularized estimation of mixture models for robust pseudo-relevance feedback
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Estimating query performance using class predictions
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
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
Reducing the risk of query expansion via robust constrained optimization
Proceedings of the 18th ACM conference on Information and knowledge management
Robust query-specific pseudo feedback document selection for query expansion
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Using statistical decision theory and relevance models for query-performance prediction
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
PageRank without hyperlinks: Structural reranking using links induced by language models
ACM Transactions on Information Systems (TOIS)
A Survey of Automatic Query Expansion in Information Retrieval
ACM Computing Surveys (CSUR)
Predicting query performance via classification
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Query performance prediction: evaluation contrasted with effectiveness
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Automatic refinement of patent queries using concept importance predictors
SIGIR '12 Proceedings of the 35th 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
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We propose a language-model-based approach for addressing the performance robustness problem -- with respect to free-parameters' values -- of pseudo-feedback-based query-expansion methods. Given a query, we create a set of language models representing different forms of its expansion by varying the parameters' values of some expansion method; then, we select a single model using criteria originally proposed for evaluating the performance of using the original query, or for deciding whether to employ expansion at all. Experimental results show that these criteria are highly effective in selecting relevance language models that are not only significantly more effective than poor performing ones, but that also yield performance that is almost indistinguishable from that of manually optimized relevance models.