  What makes a person pick certain tags over others when tagging an image? Does
the order that a person presents tags for a given image follow an implicit bias
that is personal? Can these biases be used to improve existing automated image
tagging systems? We show that tag ordering, which has been largely overlooked
by the image tagging community, is an important cue in understanding user
tagging behavior and can be used to improve auto-tagging systems. Inspired by
the assumption that people order their tags, we propose a new way of measuring
tag preferences, and also propose a new personalized tagging objective function
that explicitly considers a user's preferred tag orderings. We also provide a
(partially) greedy algorithm that produces good solutions to our new objective
and under certain conditions produces an optimal solution. We validate our
method on a subset of Flickr images that spans 5000 users, over 5200 tags, and
over 90,000 images. Our experiments show that exploiting personalized tag
orders improves the average performance of state-of-art approaches both on
per-image and per-user bases.
