Study of query expansion techniques and their application in the biomedical information retrieval.
Information Retrieval focuses on finding documents whose content matches with a user query from a large document collection. As formulating well-designed queries is difficult for most users, it is necessary to use query expansion to retrieve relevant information. Query expansion techniques are widely applied for improving the efficiency of the textual information retrieval systems. These techniques help to overcome vocabulary mismatch issues by expanding the original query with additional relevant terms and reweighting the terms in the expanded query. In this paper, different text preprocessing and query expansion approaches are combined to improve the documents initially retrieved by a query in a scientific documental database. A corpus belonging to MEDLINE, called Cystic Fibrosis, is used as a knowledge source. Experimental results show that the proposed combinations of techniques greatly enhance the efficiency obtained by traditional queries.
Department of Computer Science, Higher Technical School of Computer Engineering, University of Vigo, 32004 Ourense, Spain.
A R
AR
Rivas
Department of Computer Science, Higher Technical School of Computer Engineering, University of Vigo, 32004 Ourense, Spain.
E L
EL
Iglesias
Department of Computer Science, Higher Technical School of Computer Engineering, University of Vigo, 32004 Ourense, Spain.
L
L
Borrajo
D000465:Algorithms; D057225:Data Mining / Q000379:methods*; D003628:Database Management Systems; D016208:Databases, Factual; D016239:MEDLINE; D009323:Natural Language Processing; D014584:User-Computer Interface