Abstract
This paper represents the first participation of the Institute of Statistical Studies and Research (ISSR) at Cairo University group in CLEF 2009-Medical image retrieval track. The main objective is to improve retrieving medical image depending on associated image text. The other purpose of our participation is to experiment different text features such as article title, image caption and article paragraphs denoting to the image. We propose a simple and effective extraction method to find relevant paragraphs based on the structure of HTML files. Automatic translation of queries in different languages other than collection language is also experimented. For indexing and retrieval, we used the LEMUR toolkit. In this paper the results of 9 runs are submitted in order to compare retrieval based on different text features, as well as the effect of stop word lists and the use of relevance feedback.
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Arafa, W., Ibrahim, R. (2010). Medical Image Retrieval: ISSR at CLEF 2009. In: Peters, C., et al. Multilingual Information Access Evaluation II. Multimedia Experiments. CLEF 2009. Lecture Notes in Computer Science, vol 6242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15751-6_22
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DOI: https://doi.org/10.1007/978-3-642-15751-6_22
Publisher Name: Springer, Berlin, Heidelberg
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