Blind Relevance Feedback for the ImageCLEF Wikipedia Retrieval Task

Abstract. In this paper we will describe Berkeley’s approach to the ImageCLEF Wikipedia Retrieval task for 2010. Our approach to this task was primarily to use text-based searches on the contents of the Wikipedia image metadata records. In addition we submitted one run using a database derived from the provided “bag.xml ” set of 5000 descriptor “words ” for each image and query example images. We had also intended to combine this one image-based approach to other image-based approaches and to the text-based approaches using fusion methods, but were unable to complete the coding in time. We submitted 8 runs for ImageCLEF Wikipedia Retrieval this year, of which 6 where monolingual English, German and French with differing search areas in the metadata record, one was multilingual and the remaining one was image-based using the data derived from bag.xml file. Our best performing run was ranked 24th among the 127 submitted runs by all participants with a MAP of 0.2014, while the image-only approach was ranked dead last (one wonders, in fact, if random results might have done better).