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Semantic annotation for concept-based cross-language medical information retrieval


Volk, M; Ripplinger, B; Vintar, S; Buitelaar, P; Raileanu, D; Sacaleanu, B (2002). Semantic annotation for concept-based cross-language medical information retrieval. International Journal of Medical Informatics, 67(1-3):97-112.

Abstract

We present a framework for concept-based cross-language information retrieval in the medical domain, which is under development in the MUCHMORE pro ject. 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 to 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.

Abstract

We present a framework for concept-based cross-language information retrieval in the medical domain, which is under development in the MUCHMORE pro ject. 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 to 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.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Date:2002
Deposited On:24 Aug 2009 11:49
Last Modified:05 Apr 2016 13:19
Publisher:Elsevier
ISSN:1386-5056
Publisher DOI:https://doi.org/10.1016/S1386-5056(02)00058-8

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