Knowledge-based query expansion to support scenario-specific retrieval of medical free text

Zhenyu Liu, Wesley W. Chu
2005 Proceedings of the 2005 ACM symposium on Applied computing - SAC '05  
In retrieving medical free text, users are often interested in answers pertinent to certain scenarios that correspond to common tasks performed in medical practice, e.g., treatment or diagnosis of a disease. A major challenge in handling such queries is that scenario terms in the query (e.g., treatment) are often too general to match specialized terms in relevant documents (e.g., chemotherapy). In this paper, we propose a knowledgebased query expansion method that exploits the UMLS knowledge
more » ... rce to append the original query with additional terms that are specifically relevant to the query's scenario(s). We compared the proposed method with traditional statistical expansion that expands terms which are statistically correlated but not necessarily scenario specific. Our study on two standard testbeds shows that the knowledge-based method, by providing scenario-specific expansion, yields notable improvements over the statistical method in terms of average precision-recall. On the OHSUMED testbed, for example, the improvement is more than 5% averaging over all scenario-specific queries studied and about 10% for queries that mention certain scenarios, such as treatment of a disease and differential diagnosis of a symptom/disease. Keywords Medical information retrieval . Scenario-specific information retrieval . Knowledge-based information retrieval . Query expansion . Knowledge-based systems
doi:10.1145/1066677.1066922 dblp:conf/sac/LiuC05 fatcat:6d4qe2g4vfazto7x7enquucdjq