Journal of Digital Imaging

, Volume 24, Issue 1, pp 160–164 | Cite as

Ontology-Assisted Analysis of Web Queries to Determine the Knowledge Radiologists Seek

  • Daniel L. Rubin
  • Adam Flanders
  • Woojin Kim
  • Khan M. Siddiqui
  • Charles E. KahnJr


Radiologists frequently search the Web to find information they need to improve their practice, and knowing the types of information they seek could be useful for evaluating Web resources. Our goal was to develop an automated method to categorize unstructured user queries using a controlled terminology and to infer the type of information users seek. We obtained the query logs from two commonly used Web resources for radiology. We created a computer algorithm to associate RadLex-controlled vocabulary terms with the user queries. Using the RadLex hierarchy, we determined the high-level category associated with each RadLex term to infer the type of information users were seeking. To test the hypothesis that the term category assignments to user queries are non-random, we compared the distributions of the term categories in RadLex with those in user queries using the chi square test. Of the 29,669 unique search terms found in user queries, 15,445 (52%) could be mapped to one or more RadLex terms by our algorithm. Each query contained an average of one to two RadLex terms, and the dominant categories of RadLex terms in user queries were diseases and anatomy. While the same types of RadLex terms were predominant in both RadLex itself and user queries, the distribution of types of terms in user queries and RadLex were significantly different (p < 0.0001). We conclude that RadLex can enable processing and categorization of user queries of Web resources and enable understanding the types of information users seek from radiology knowledge resources on the Web.

Key words

Ontologies terminologies vocabularies RadLex software tools controlled vocabulary natural language processing web technology 



The authors thank the American Roentgen Ray Society and iVirtuoso Inc. for access to the query logs. This work was supported in part by the American Roentgen Ray Society.


  1. 1.
    Bodenreider O, Stevens R: Bio-ontologies: current trends and future directions. Brief Bioinform 7:256–274, 2006CrossRefPubMedGoogle Scholar
  2. 2.
    Rubin DL, Shah NH, Noy NF: Biomedical ontologies: a functional perspective. Brief Bioinform 9:75–90, 2008CrossRefPubMedGoogle Scholar
  3. 3.
    Langlotz CP: RadLex: a new method for indexing online educational materials. Radiographics 26:1595–1597, 2006CrossRefPubMedGoogle Scholar
  4. 4.
    Kundu S, et al: The IR RadLex project: an interventional radiology lexicon–a collaborative project of the Radiological Society of North America and the Society of Interventional Radiology. J Vasc Interv Radiol 20:433–435, 2009CrossRefPubMedGoogle Scholar
  5. 5.
    Gennari JH, et al: The evolution of Protege: an environment for knowledge-based systems development. Int J Human-Comput Stud 58:89–123, 2003CrossRefGoogle Scholar
  6. 6.
    Rubin DL, Noy NF, Musen MA: Protege: a tool for managing and using terminology in radiology applications. J Digit Imaging 20(Suppl 1):34–46, 2007CrossRefPubMedGoogle Scholar
  7. 7.
    Shah NH, Rubin DL, Espinosa I, Montgomery K, Musen MA: Annotation and query of tissue microarray data using the NCI Thesaurus. BMC Bioinformatics 8:296, 2007CrossRefPubMedGoogle Scholar
  8. 8.
    Kahn Jr, CE, Channin DS, Rubin DL: An ontology for PACS integration. J Digit Imaging 19:316–327, 2006CrossRefPubMedGoogle Scholar

Copyright information

© Society for Imaging Informatics in Medicine 2010

Authors and Affiliations

  • Daniel L. Rubin
    • 1
  • Adam Flanders
    • 2
  • Woojin Kim
    • 3
  • Khan M. Siddiqui
    • 4
    • 5
  • Charles E. KahnJr
    • 6
  1. 1.Department of RadiologyStanford University, Richard M. Lucas CenterStanfordUSA
  2. 2.Thomas Jefferson UniversityPhiladelphiaUSA
  3. 3.Radiology, University of PennsylvaniaPhiladelphiaUSA
  4. 4.VA Maryland Healthcare SystemBaltimoreUSA
  5. 5.Health Solutions GroupMicrosoft CorporationRedmondUSA
  6. 6.Radiology, Medical College of WisconsinMilwaukeeUSA

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