MLIAM: MUCHMORE: Multilingual Concept Hierarchies for Medical Information Organization and Retrieval

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This project will extend the state of the art in high performance multilingual information access, both in terms of underlying science and its technological realization via a functional prototype for English and German in the biomedical domain. Heretofore, Cross-Lingual Information Retrieval (CLIR) was founded upon dictionary-based query translation methods or corpus-based statistical learning of vocabulary mappings, combined with various IR methods. The existence of large, well accepted ontological resources in biomedicine (e.g., MeSH and UMLS) enables a new interlingual approach wherein both queries and documents are mapped into multiple taxonomic categories automatically, permitting direct conceptual matching. This research will compare existing techniques (dictionarybased and corpus-based) with the new interlingual methods on various evaluative dimensions, such as I I-point average precision, computational tractability, and end-to-end user acceptability. To judge the latter, a full prototype system will be developed; that is the main focus of the European side of the project. In addition to developing and evaluating these new CLIR methods, and producing and evaluating a usable prototype application, this project will provide other benefits beyond CLIR proper improving IR precision via automated corpus-based word sense disambiguation; developing statistical methods for the creation of multilingual lexical and phrasal resources; providing automated on-demand summarization of retrieved documents using the Maximal Marginal Relevance method; and improving multilingual information access and management systems forthe biomedical domain.