Pivoted document length normalization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Combining classifiers in text categorization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Content-based query of image databases: inspirations from text retrieval
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Query translation by text categorization
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Term proximity scoring for keyword-based retrieval systems
ECIR'03 Proceedings of the 25th European conference on IR research
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
Hi-index | 0.00 |
We present the fusion of simple retrieval strategies with thesaural resources to perform document and query translation by text categorisation for cross-language retrieval in a collection of medical images with case notes. The collection includes documents in French, English and German. The fusion of visual and textual content is also treated. Unlike most automatic categorisation systems our approach can be applied with any controlled vocabulary and does not require training data. For the experiments we use Medical Subject Headings (MeSH), a terminology maintained by the National Library of Medicine existing in 12 languages. The idea is to annotate every text of the collection (documents and queries) with a set of MeSH terms using our automatic text categoriser. Our results confirm that such an approach is competitive. Simple linear approaches were used to combine text and visual features.