How doctors search: A study of query behaviour and the impact on search results

  • Authors:

  • Marianne Lykke;Susan Price;Lois Delcambre

  • Affiliations:

  • Aalborg University Nyhavnsgade 14, Room 3-16, 9000 Aalborg, Denmark;Microsoft Corporation, One Microsoft Way, Redmond, WA 98052, USA;Portland State University, Department of Computer Science, P.O. Box 751, Portland, OR 97207-0751, United States

  • Venue:
  • Information Processing and Management: an International Journal
  • Year:
  • 2012

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Abstract

Professional, workplace searching is different from general searching, because it is typically limited to specific facets and targeted to a single answer. We have developed the semantic component (SC) model, which is a search feature that allows searchers to structure and specify the search to context-specific aspects of the main topic of the documents. We have tested the model in an interactive searching study with family doctors with the purpose to explore doctors' querying behaviour, how they applied the means for specifying a search, and how these features contributed to the search outcome. In general, the doctors were capable of exploiting system features and search tactics during the searching. Most searchers produced well-structured queries that contained appropriate search facets. When searches failed it was not due to query structure or query length. Failures were mostly caused by the well-known vocabulary problem. The problem was exacerbated by using certain filters as Boolean filters. The best working queries were structured into 2-3 main facets out of 3-5 possible search facets, and expressed with terms reflecting the focal view of the search task. The findings at the same time support and extend previous results about query structure and exhaustivity showing the importance of selecting central search facets and express them from the perspective of search task. The SC model was applied in the highest performing queries except one. The findings suggest that the model might be a helpful feature to structure queries into central, appropriate facets, and in returning highly relevant documents.