A Comparison of Content-Based Tag Recommendations in Folksonomy Systems
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Knowledge Processing and Data Analysis, volume 6581 of Lecture Notes in Computer Science, page 136--149. Berlin/Heidelberg, Springer, (2011)

Recommendation algorithms and multi-class classifiers can support users of social bookmarking systems in assigning tags to their bookmarks. Content based recommenders are the usual approach for facing the cold start problem, i.e., when a bookmark is uploaded for the first time and no information from other users can be exploited. In this paper, we evaluate several recommendation algorithms in a cold-start scenario on a large real-world dataset.
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