A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
An Introduction to Variational Methods for Graphical Models
Machine Learning
Vector-space ranking with effective early termination
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Static index pruning for information retrieval systems
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
A study of smoothing methods for language models applied to Ad Hoc information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Dependence language model for information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Optimization strategies for complex queries
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
A Markov random field model for term dependencies
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Integer linear programming inference for conditional random fields
ICML '05 Proceedings of the 22nd international conference on Machine learning
Term proximity scoring for ad-hoc retrieval on very large text collections
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
The impact of caching on search engines
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Pruning policies for two-tiered inverted index with correctness guarantee
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Automatic feature selection in the markov random field model for information retrieval
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Best-Effort Top-k Query Processing Under Budgetary Constraints
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
An improved markov random field model for supporting verbose queries
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Reducing the risk of query expansion via robust constrained optimization
Proceedings of the 18th ACM conference on Information and knowledge management
Learning concept importance using a weighted dependence model
Proceedings of the third ACM international conference on Web search and data mining
Early exit optimizations for additive machine learned ranking systems
Proceedings of the third ACM international conference on Web search and data mining
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
A cascade ranking model for efficient ranked retrieval
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Parameterized concept weighting in verbose queries
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Learning to rank under tight budget constraints
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Effective query formulation with multiple information sources
Proceedings of the fifth ACM international conference on Web search and data mining
Besting the quiz master: crowdsourcing incremental classification games
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Slow Search: Information Retrieval without Time Constraints
Proceedings of the Symposium on Human-Computer Interaction and Information Retrieval
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This paper introduces the notion of temporally constrained ranked retrieval, which, given a query and a time constraint, produces the best possible ranked list within the specified time limit. Naturally, more time should translate into better results, but the ranking algorithm should always produce some results. This property is desirable from a number of perspectives: to cope with diverse users and information needs, as well as to better manage system load and variance in query execution times. We propose two temporally constrained ranking algorithms based on a class of probabilistic prediction models that can naturally incorporate efficiency constraints: one that makes independent feature selection decisions, and the other that makes joint feature selection decisions. Experiments on three different test collections show that both ranking algorithms are able to satisfy imposed time constraints, although the joint model outperforms the independent model in being able to deliver more effective results, especially under tight time constraints, due to its ability to capture feature dependencies.