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

Carnegie Mellon University, Pittsburgh PA

Investigators

Abstract

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.