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The Xtrieval Framework at CLEF 2008: ImageCLEF Photographic Retrieval Task

This paper describes our participation at the ImageCLEF photographic retrieval task. We used our Xtrieval framework for the preparation and execution of the experiments. This year, we submitted 4 experiments in total. The experiments showed that our thesaurus based query expansions works well in improving the geometric mean average precision (GMAP) and binary preference (BPREF), but deteriorates the improvements gained by the addition of content-based image retrieval. The baseline (text-only) scored a mean average precision (MAP) of 0.0998. The combination of text and image retrieval gained a raise by 37 percent to a MAP of 0.1364. After applying the query expansion to both experiments the MAP for the text-only retrieval increased to 0.1081, but the MAP for the combined text and image retrieval decreased to 0.1140. By implementing an interface to the PostgreSQL database the retrieval speed and comparison operations for vectors could be speeded up.