Leveraging multi-faceted tagging to improve search in folksonomy systems

Abstract

In this paper we present ranking algorithms for folksonomy systems that exploit additional contextual information attached to tag assignments available. We evaluate the algorithms in the TagMe! system, a tagging front-end for Flickr, and show that our algorithms, which exploit categories, spatial information, and URIs describing the semantics of tag assignments, perform significantly better than the FolkRank that does not consider such contextual information.