Semantic annotation for concept-based cross-language medical information retrieval.
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.
Volk
Martin
M
Eurospider Information Technology AG, Schaffhauserstrasse 18, CH-8006, Zürich, Switzerland. volk@eurospider.com
Ripplinger
Bärbel
B
Vintar
Spela
S
Buitelaar
Paul
P
Raileanu
Diana
D
Sacaleanu
Bogdan
B
D006801:Humans; D016247:Information Storage and Retrieval; D007256:Information Systems; D008037:Linguistics; D009323:Natural Language Processing; D012660:Semantics; D017432:Unified Medical Language System