Pivoted document length normalization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Relevance ranking for one to three term queries
Information Processing and Management: an International Journal
A probabilistic model of information retrieval: development and comparative experiments
Information Processing and Management: an International Journal
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
Biterm language models for document retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
A maximum entropy approach to identifying sentence boundaries
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Dependence language model for information retrieval
Proceedings of the 27th 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
A generative theory of relevance
A generative theory of relevance
Effective self-training for parsing
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Linear feature-based models for information retrieval
Information Retrieval
The smoothed dirichlet distribution: understanding cross-entropy ranking in information retrieval
The smoothed dirichlet distribution: understanding cross-entropy ranking in information retrieval
Latent concept expansion using markov random fields
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
MRF based approach for sentence retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A comparison of statistical significance tests for information retrieval evaluation
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Learning to rank for information retrieval (LR4IR 2007)
ACM SIGIR Forum
Effective and efficient user interaction for long queries
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Discovering key concepts in verbose queries
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Boosting web retrieval through query operations
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Learning concept importance using a weighted dependence model
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
Exploring reductions for long web queries
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Ranking under temporal constraints
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Improving verbose queries using subset distribution
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Parameterized concept weighting in verbose queries
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
Query aspect based term weighting regularization in information retrieval
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Generating reformulation trees for complex queries
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Generating queries from user-selected text
Proceedings of the 4th Information Interaction in Context Symposium
Learning lexicon models from search logs for query expansion
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Modeling term dependencies with quantum language models for IR
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Towards Concept-Based Translation Models Using Search Logs for Query Expansion
Proceedings of the 21st ACM international conference on Information and knowledge management
Semantic concept-enriched dependence model for medical information retrieval
Journal of Biomedical Informatics
| Hi-index | 0.00 |
Recent work in supervised learning of term-based retrieval models has shown significantly improved accuracy can often be achieved via better model estimation. In this paper, we show retrieval accuracy with Metzler and Croft's Markov random field (MRF) approach can be similarly improved via supervised learning. While the original MRF method estimates a parameter for each of its three feature classes from data, parameters within each class are set via a uniform weighting scheme adopted from the standard unigram. We conjecture greater MRF retrieval accuracy should be possible by better estimating within-class parameters, particularly for verbose queries employing natural language terms. Retrieval experiments with these queries on three TREC document collections show our improved MRF consistently out-performs both the original MRF and supervised unigram baselines. Additional experiments using blind-feedback and evaluation with optimal weighting demonstrate both the immediate value and further potential of our method.