Experiments in cross-language medical information retrieval using a mixing translation module

Abstract

Given the ever-increasing scale and diversity of medical literature widely published in English on the Internet, improving the performance of information retrieval by cross-language is an urgent research objective. Cross-language medical information retrieval (CLMIR) consists of providing a query in one language and searching medical document collections in one or more different languages. Our users of CLMIR are users who are able to read biomedical texts in English, but have difficulty formulating English queries. This paper proposes a French/English CLMIR system as a mixing model for supporting the retrieval of English medical documents. Methods fall into the category of query translation approach in which we use a hybrid machine translation that combines a pattern-based module with a rule-based translator and includes three steps from pre- to- post-translation. In parallel to this hybrid machine translation, we use multilingual UMLS Methasaurus as a complementary translator. The results show that using a mixing translation module outperforms machine translation-based method and thesaurus-based method used separately.