Speaker: Neela Sawant
Title: Personalized tag recommendation using local interaction network

Abstract: Typical tag recommendation systems for photos shared on
social networks such as Flickr, use visual content analysis,
collaborative filtering or personalization strategies to recommend
annotations. However, the dependence on manual intervention and the
knowledge of sufficient personal preferences coupled with the
folksonomic issues limit the scope of these strategies. In this talk,
I will discuss an automatic and folksonomic model that can recommend
tags for a user's photos without an explicit knowledge of the user's
personal tagging preferences. The model is learned using the
collective tagging behavior of other users in the user's local
interaction network, which we believe approximates the user's
preferences, at least partially. The tag recommendation model
generates controlled content-based annotations and then uses a Naive
Bayes formulation to translate these annotations to a set of
folksonomic tags selected from the tags used by the local interaction
network.