Improving Web Image Search using Meta Re-rankers

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Provided by: International Journal for Development of Computer Science & Technology (IJDCST)
Topic: Big Data
Format: PDF
The previous methods for image search reranking suffer from the unreliability of the assumptions under which the initial text based image search result is employed in the reranking process. In the authors' proposed system, prototype-based reranking method is suggested address this problem in scalable fashion. This typical assumption that the top-images in the text-based search result are equally relevant is relaxed by linking the relevance of the images to their initial rank positions. The number of images is employed by the initial search result as the prototypes that serve to visually represent the query and that are subsequently used to construct meta re-rankers.
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