Reader's models of text structures: the case of academic articles
International Journal of Man-Machine Studies
Document structure and digital libraries: how researchers mobilize information in journal articles
Information Processing and Management: an International Journal - Special issue on progress toward digital libraries
A knowledge-based approach to organizing retrieved documents
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Integrating automatic genre analysis into digital libraries
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
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
Using semantic components to facilitate access to domain-specific documents in government settings
dg.o '06 Proceedings of the 2006 international conference on Digital government research
Semantic components enhance retrieval of domain-specific documents
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Journal of Information Science
Moving toward web-scale: adapting semantic components for use in large collections
FDIA'07 Proceedings of the 1st BCS IRSG conference on Future Directions in Information Access
How doctors search: A study of query behaviour and the impact on search results
Information Processing and Management: an International Journal
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Inability to find answers to clinical questions is a major obstacle to obtaining just-in-time information during patient encounters. We have introduced a new model for describing the content of documents in domain-specific collections, using document classes and semantic components, that may supplement existing indexing and searching techniques and improve information retrieval. In this paper we describe the model and present the results of our investigations into using the model to represent clinical questions in the medical domain. We manually mapped generic questions from a clinical question taxonomy to two web-based document collections using the document classes and semantic components we identified for each collection. We successfully mapped 36 of 50 question categories in one resource, and 34 of 50 in the other. Based on the frequency of the question types in the taxonomy, over 92% of questions were covered by the mappings in both resources. We conclude that our model is capable of usefully representing information needs and we propose ways to use the model for retrieval.