How Effective is Stemming and Decompounding for German Text Retrieval?
Information Retrieval
Dictionary-based techniques for cross-language information retrieval
Information Processing and Management: an International Journal - Special issue: Cross-language information retrieval
Bootstrapping dictionaries for cross-language information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Overview of the ImageCLEFmed 2006 medical retrieval and medical annotation tasks
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
Combining CBIR and NLP for multilingual terminology alignment and cross-language image indexing
YIWCALA '10 Proceedings of the NAACL HLT 2010 Young Investigators Workshop on Computational Approaches to Languages of the Americas
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In the 2006 ImageCLEF Medical Image Retrieval task we evaluate the effects of deep morphological analysis for mono-and cross-lingual document retrieval in the biomedical domain. The morphological analysis is based on the MorphoSaurus system in which subwords are introduced as morphologically meaningful word units. Subwords are organized in language specific lexica that were partly manually and partly automatically generated and currently cover six European languages. They are linked together in a multilingual thesaurus. The use of subwords instead of full words significantly reduces the number of lexical entries that are needed to sufficiently cover a specific language and domain. A further benefit of the approach is its independence from the underlying retrieval system. We combined MorphoSaurus with the open-source search engine Lucene and achieved precision gains of up to 25% over the baseline for a monolingual setting and promising results in a multilingual scenario.