A Ubiquitous Image Tagging System Using User Context

Tagging is nowadays the most predominant technique to make resources searchable. These allow users to create and manage tags to annotate and categorize content. In this paper, we propose an approach to tag images in a user's collection based upon user's personal profile, his/her social context and the context defined by his/her prior image collection. We apply LDA for context modeling. In this scheme, tag similarity and tag relevance are jointly estimated so that they can profit from each other. We have used an Adaptive Context Model created from user related sources to tag images. Experimental validation with user's mobile as well as website based image collection has established effectiveness of the approach.