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Query Reformulation with Information-Based Query Expansion for Handling Medical Scenario Queries
Abstract
In this paper, I propose an information-based query expansion technique to support scenario specific retrieval in the medical domain. An information-based query expansion technique takes advantage of the UMLS (United Medical Language System) information source to append the original query with additional terms that are specifically relevant to the query’s scenario, thus improving upon traditional query expansion approaches. I compare this technique with cross-search method that only refer to the encyclopedia and expand terms that are not necessarily scenario specific. The study on the clinical notes shows that the information based techniques that results in scenario-based expansion outperformed over the cross-search and automatic query expansion method on average in all categories of scenarios.
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