Online photo sharing systems, such as Flickr and Picasa, provide a valuable source of human-annotated photos. Textual annotations are used not only to describe the visual content of an image, but also subjective, spatial, temporal and social dimensions, complicating the task of keywordbased search. In this paper we investigate a method that exploits visual annotations, e.g. notes in Flickr, to enhance keyword-based systems retrieval performance. For this purpose we adopt the bag-of-visual-words

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... approach for contentbased image retrieval as our baseline. We then apply rank aggregation of the top 25 results obtained with a set of visual annotations that match the keyword-based query. The results on retrieval experiments show significant improvements in retrieval performance when comparing the aggregated approach with our baseline, which also slightly outperforms text-only search. When using a textual filter on the search space in combination with the aggregated approach an additional boost in retrieval performance is observed, which underlines the need for large scale content-based image retrieval techniques to complement the text-based search.