Abstract
In this paper we explain experiments in the medical information retrieval task (ImageCLEFmed). We experimented with query expansion and the amount of textual information obtained from the collection. For expansion, we carried out experiments using MeSH ontology and UMLS separately. With respect to textual collection, we produced three different collections, the first one with caption and title, the second one with caption, title and the text of the section where the image appears, and the third one with the full text article. Moreover, we experimented with textual and visual search, along with the combination of these two results. For image retrieval we used the results generated by the FIRE software. The best results were obtained using MeSH query expansion on shortest textual collection (only caption and title) merging with the FIRE results.
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Díaz-Galiano, M.C., García-Cumbreras, M.A., Martín-Valdivia, M.T., Ureña-López, L.A., Montejo-Ráez, A. (2009). Query Expansion on Medical Image Retrieval: MeSH vs. UMLS. In: Peters, C., et al. Evaluating Systems for Multilingual and Multimodal Information Access. CLEF 2008. Lecture Notes in Computer Science, vol 5706. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04447-2_94
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DOI: https://doi.org/10.1007/978-3-642-04447-2_94
Publisher Name: Springer, Berlin, Heidelberg
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