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Towards Improving Search Results for Medical Experts and Laypersons

Conference paper
Authors Karin Friberg Heppin
Anni Järvelin
Published in Proceedings of CLEFeHealth 2012
Publication year 2012
Published at Department of Swedish
Language en
Keywords medical informatics, eHealth, information retrieval, user groups
Subject categories Language Technology (Computational Linguistics), Computational linguistics, Information science


In a domain such as medicine, it is important that individuals’ infor-mation needs are met with information on a suitable level of difficulty and ex-pertise. This paper focuses on facilitating medical information access through reformulating queries and re-ranking result lists utilizing features typical for the language written for professionals or for laypersons. The aim is to produce re-sult lists where the ranking is better suited for the expertise level of the user. We will explore the possibility of using features such as trigger phrases for que-ry reformulation and document length, average word length or compound ratio for re-ranking. The Swedish medical IR test collection, MedEval, from Språkbanken, Uni-versity of Gothenburg, will be used to find features specific for professional language and lay language and to study the effectiveness of these features in re-formulating queries and re-ranking search results based on the target group. The test collection contains 42,250 documents from the medical corpus MedLex , collected from all types of written medical information found in electronic for-mat, except patient records. The collection contains 62 topics. In total, 7,044 documents have been assessed both for relevance to these topics and for tar-get group. Our experiments will be based on earlier explorative studies on medical ex-pert and lay language where some features were identified. It was found that documents written for professionals tended to have more tokens per document, longer words, and more compounds than lay documents.

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