We present a system for personalized tag suggestion for Flickr: While the user is entering/selecting new tags for a particular picture, the system is suggesting related tags to her, based on the tags that she or other people have used in the past along with (some of) the tags already entered. The suggested tags are dynamically updated with every additional tag entered/selected. We describe three algorithms which can be applied to this problem. In experiments, our best-performing method yields an improvement in precision of 10-15% over a baseline method very similar to the system currently used by Flickr. Our system is accessible at http://ltaa5.epfl.ch/flickr-tags/. To the best of our knowledge, this is the first study on tag suggestion in a setting where (i) no full text information is available, such as for blogs, (ii) no item has been tagged by more than one person, such as for social bookmarking sites, and (iii) suggestions are dynamically updated, requiring efficient yet effective algorithms.