Tag Ranking by Linear Relational Neighbourhood Propagation

摘要

We propose a tag recommendation method which can assist users in tagging process by suggesting relevant tags. % or directly expand the set of tags. The method is based on query-based ranking on relational multi-type graphs which capture the annotation relationship between objects and tags, as well as the object similarity and tag correlation. The additional advance consists in extending the linear neighbourhood propagation to the relational graphs with the Laplacian regularization framework. We report evaluation results on a large-scale Flickr data set.