Using WordNet to disambiguate word senses for text retrieval
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using lexical-semantic relations
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Word sense disambiguation and information retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A vector space model for automatic indexing
Communications of the ACM
Workshop on patent retrieval SIGIR 2000 workshop report
ACM SIGIR Forum
Probabilistic models of information retrieval based on measuring the divergence from randomness
ACM Transactions on Information Systems (TOIS)
Natural language question answering: the view from here
Natural Language Engineering
Journal of Biomedical Informatics - Special issue: Unified medical language system
Dependence language model for information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Information retrieval using word senses: root sense tagging approach
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
The NRRC reliable information access (RIA) workshop
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Combining the language model and inference network approaches to retrieval
Information Processing and Management: an International Journal - Special issue: Bayesian networks and information retrieval
Performance issues and error analysis in an open-domain Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Question answering passage retrieval using dependency relations
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Modeling task-genre relationships for IR in the workplace
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
Semantic indexing using WordNet senses
RANLPIR '00 Proceedings of the ACL-2000 workshop on Recent advances in natural language processing and information retrieval: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 11
Question answering based on semantic structures
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Answering Clinical Questions with Knowledge-Based and Statistical Techniques
Computational Linguistics
Answering Clinical Questions with Knowledge-Based and Statistical Techniques
Computational Linguistics
The role of information retrieval in answering complex questions
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Presentation schemes for component analysis in IR experiments
ACM SIGIR Forum
Knowledge-intensive conceptual retrieval and passage extraction of biomedical literature
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Extended probabilistic HAL with close temporal association for psychiatric query document retrieval
ACM Transactions on Information Systems (TOIS)
A system for finding biological entities that satisfy certain conditions from texts
Proceedings of the 17th ACM conference on Information and knowledge management
Categorisation of web documents using extraction ontologies
International Journal of Metadata, Semantics and Ontologies
Vaidurya: A multiple-ontology, concept-based, context-sensitive clinical-guideline search engine
Journal of Biomedical Informatics
A methodology for engineering ontology acquisition and validation
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Biomedical question answering: A survey
Computer Methods and Programs in Biomedicine
Medical query generation by term-category correlation
Information Processing and Management: an International Journal
AskHERMES: An online question answering system for complex clinical questions
Journal of Biomedical Informatics
Using SKOS vocabularies for improving web search
Proceedings of the 22nd international conference on World Wide Web companion
PICO element detection in medical text without metadata: Are first sentences enough?
Journal of Biomedical Informatics
Semantic concept-enriched dependence model for medical information retrieval
Journal of Biomedical Informatics
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Despite its intuitive appeal, the hypothesis that retrieval at the level of "concepts" should outperform purely term-based approaches remains unverified empirically. In addition, the use of "knowledge" has not consistently resulted in performance gains. After identifying possible reasons for previous negative results, we present a novel framework for "conceptual retrieval" that articulates the types of knowledge that are important for information seeking. We instantiate this general framework in the domain of clinical medicine based on the principles of evidence-based medicine (EBM). Experiments show that an EBM-based scoring algorithm dramatically outperforms a state-of-the-art baseline that employs only term statistics. Ablation studies further yield a better understanding of the performance contributions of different components. Finally, we discuss how other domains can benefit from knowledge-based approaches.