ACOS'07 Proceedings of the 6th Conference on WSEAS International Conference on Applied Computer Science - Volume 6
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Tag Recommendations in Folksonomies
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
GroupMe! - where semantic web meets web 2.0
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Context-based ranking in folksonomies
Proceedings of the 20th ACM conference on Hypertext and hypermedia
Social tagging in recommender systems: a survey of the state-of-the-art and possible extensions
Artificial Intelligence Review
Generating resource profiles by exploiting the context of social annotations
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
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Folksonomy systems enable users to participate in the Webcontent creation process by annotating (tagging) resourceswith freely chosen keywords. Still, it is an open issue howto exploit this user-created content, and how to processand use these emergent semantics effectively. We investigatehow the context of Web resources can be utilizedto improve recommender strategies in social tagging systems.We focus on the GroupMe! system, which enablesusers to create groups in order to bundle Web resources.GroupMe! groups form valuable context information forthe resources contained in such groups. In this paper we exploitgraph-based tag recommendation strategies, evaluatethem in the GroupMe! dataset, and benchmark our resultsagainst other approaches. In our evaluations we show thatgraph-based strategies outperform other approaches, andshow the immanent benefit of graph-based recommendationstrategies which exploit the group context for recommendingtags to untagged resources.