Online photo services such as Flickr and Zooomr allow users
to share their photos with family, friends, and the online
community at large. An important facet of these services
is that users manually annotate their photos using so called
tags, which describe the contents of the photo or provide
additional contextual and semantical information. In this
paper we investigate how we can assist users in the tagging
phase. The contribution of our research is twofold. We
analyse a representative snapshot of Flickr and present the
results by means of a tag characterisation focussing on how
users tags photos and what information is contained in the
tagging. Based on this analysis, we present and evaluate tag
recommendation strategies to support the user in the photo
annotation task by recommending a set of tags that can be
added to the photo. The results of the empirical evaluation
show that we can effectively recommend relevant tags for a
variety of photos with different levels of exhaustiveness of
original tagging.
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