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Assisting consumer health information retrieval with query recommendations
Qing T Zeng1, Jonathan Crowell, Robert M Plovnick
1Department of Radiology, Decision Systems Group, Thorn 309, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA. qzeng@dsg.bwh.harvard.edu
Objective:
Health information retrieval (HIR) on the Internet has become an important practice for millions of people, many of whom have problems forming effective queries. We have developed and evaluated a tool to assist people in health-related query formation.
Design:
We developed the Health Information Query Assistant (HIQuA) system. The system suggests alternative/additional query terms related to the user's initial query that can be used as building blocks to construct a better, more specific query. The recommended terms are selected according to their semantic distance from the original query, which is calculated on the basis of concept co-occurrences in medical literature and log data as well as semantic relations in medical vocabularies.
Measurements:
An evaluation of the HIQuA system was conducted and a total of 213 subjects participated in the study. The subjects were randomized into 2 groups. One group was given query recommendations and the other was not. Each subject performed HIR for both a predefined and a self-defined task.
Results:
The study showed that providing HIQuA recommendations resulted in statistically significantly higher rates of successful queries (odds ratio = 1.66, 95% confidence interval = 1.16-2.38), although no statistically significant impact on user satisfaction or the users' ability to accomplish the predefined retrieval task was found.
Conclusion:
Providing semantic-distance-based query recommendations can help consumers with query formation during HIR.
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