Volk Martin, Ripplinger Bärbel, Vintar Spela, Buitelaar Paul, Raileanu Diana, Sacaleanu Bogdan
Eurospider Information Technology AG, Schaffhauserstrasse 18, CH-8006, Zürich, Switzerland.
Int J Med Inform. 2002 Dec 4;67(1-3):97-112. doi: 10.1016/s1386-5056(02)00058-8.
We present a framework for concept-based cross-language information retrieval in the medical domain, which is under development in the MUCHMORE project. Our approach is based on using the Unified Medical Language System (UMLS) as the primary source of semantic data. Documents and queries are annotated with multiple layers of linguistic information. Linguistic processing includes part-of-speech tagging, morphological analysis, phrase recognition and the identification of medical terms and semantic relations between them. The paper describes experiments in monolingual and cross-language document retrieval, performed on a corpus of medical abstracts. Results show that linguistic processing, especially lemmatization and compound analysis for German, is a crucial step in achieving a good baseline performance. On the other hand, they show that semantic information, specifically the combined use of concepts and relations, increases the performance in monolingual and cross-language retrieval.
我们提出了一个用于医学领域基于概念的跨语言信息检索的框架，该框架正在MUCHMORE项目中开发。我们的方法基于将统一医学语言系统（UMLS）用作语义数据的主要来源。文档和查询用多层语言信息进行标注。语言处理包括词性标注、形态分析、短语识别以及医学术语及其之间语义关系的识别。本文描述了在医学摘要语料库上进行的单语言和跨语言文档检索实验。结果表明，语言处理，特别是德语的词元化和复合分析，是实现良好基线性能的关键步骤。另一方面，结果表明语义信息，特别是概念和关系的联合使用，提高了单语言和跨语言检索的性能。
