| Title |
Ontology-Assisted Analysis of Web Queries to Determine the Knowledge Radiologists Seek
|
|---|---|
| Published in |
Journal of Digital Imaging, March 2010
|
| DOI | 10.1007/s10278-010-9289-2 |
| Pubmed ID | |
| Authors |
Daniel L. Rubin, Adam Flanders, Woojin Kim, Khan M. Siddiqui, Charles E. Kahn |
| Abstract |
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. |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 7% |
| Colombia | 1 | 3% |
| Germany | 1 | 3% |
| Unknown | 25 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 21% |
| Student > Master | 5 | 17% |
| Student > Ph. D. Student | 5 | 17% |
| Professor | 4 | 14% |
| Professor > Associate Professor | 3 | 10% |
| Other | 4 | 14% |
| Unknown | 2 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 13 | 45% |
| Medicine and Dentistry | 7 | 24% |
| Engineering | 2 | 7% |
| Business, Management and Accounting | 1 | 3% |
| Social Sciences | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 2 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 April 2012.
All research outputs
#20,165,369
of 22,675,759 outputs
Outputs from Journal of Digital Imaging
#929
of 1,045 outputs
Outputs of similar age
#90,917
of 95,433 outputs
Outputs of similar age from Journal of Digital Imaging
#8
of 9 outputs
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