The effect multiple query representations on information retrieval system performance
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This paper deals with information retrieval from visual databases. We propose an approach based on multiple representations, multiple queries, and the fusion of results returned by these different representations and queries. The basic idea of data fusion in information retrieval is to use several models, several representations, several search strategies, several queries, etc., and then fuse (merge) the results returned by each model, representation, strategy or query in a unique list of results by using appropriate fusion models. Doing so, retrieval effectiveness should be improved without necessarily altering, in an important way, retrieval efficiency. We consider both the general retrieval case as well as the invariant retrieval case. We consider the case of textures in particular. Benchmarking carried out on two (2) image databases shows that retrieval relevance is improved in a very appreciable way with the fused model.