Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
AutoTag: a collaborative approach to automated tag assignment for weblog posts
Proceedings of the 15th international conference on World Wide Web
REFEREE: an open framework for practical testing of recommender systems using ResearchIndex
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Tag recommendations in social bookmarking systems
AI Communications
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
LDA for on-the-fly auto tagging
Proceedings of the fourth ACM conference on Recommender systems
The social bookmark and publication management system bibsonomy
The VLDB Journal — The International Journal on Very Large Data Bases
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The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on the evaluation and development of appropriate methods rather than tackling the practical challenges of how to integrate recommendation methods into real tagging systems, record and evaluate their performance. In this paper we describe the tag recommendation framework we developed for our social bookmark and publication sharing system BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. Furthermore, this paper presents a first evaluation of two exemplarily deployed recommendation methods.