Conference proceedings article
A Comparison of content-based Tag Recommendations in Folksonomy Systems



Publication Details
Authors:
Jäschke, R.; Stumme, G.; Hotho, A.; Illig, J.
Editor:
Wolff Erich Karl, Palchunov E. Dmitry, Zagoruiko G. Nikolay, Andelfinger Urs
Publisher:
Springer
Place:
Berlin/Heidelberg
Publication year:
2011
Pages range:
136-149
Book title:
Postproceedings of the International Conference on Knowledge Processing in Practice (KPP 2007)
Title of series:
Lecture Notes in Computer Science

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


Keywords
folksonomy, recommender, tag

Last updated on 2019-25-07 at 17:08