GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
The Benefit of Using Tag-Based Profiles
LA-WEB '07 Proceedings of the 2007 Latin American Web Conference
Discovering shared conceptualizations in folksonomies
Web Semantics: Science, Services and Agents on the World Wide Web
Tag-aware recommender systems by fusion of collaborative filtering algorithms
Proceedings of the 2008 ACM symposium on Applied computing
Personalized search and exploration with mytag
Proceedings of the 17th international conference on World Wide Web
Tag recommendations based on tensor dimensionality reduction
Proceedings of the 2008 ACM conference on Recommender systems
Can all tags be used for search?
Proceedings of the 17th ACM conference on Information and knowledge management
Explorations in tag suggestion and query expansion
Proceedings of the 2008 ACM workshop on Search in social media
Folksonomy-Based Collabulary Learning
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Tag recommendations in social bookmarking systems
AI Communications
Scalable Tensor Decompositions for Multi-aspect Data Mining
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Cross system personalization by learning manifold alignments
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Linkage, aggregation, alignment and enrichment of public user profiles with Mypes
Proceedings of the 6th International Conference on Semantic Systems
LDA for on-the-fly auto tagging
Proceedings of the fourth ACM conference on Recommender systems
Recommendation of similar users, resources and social networks in a Social Internetworking Scenario
Information Sciences: an International Journal
Unsupervised auto-tagging for learning object enrichment
EC-TEL'11 Proceedings of the 6th European conference on Technology enhanced learning: towards ubiquitous learning
Mining tweets for tag recommendation on social media
Proceedings of the 3rd international workshop on Search and mining user-generated contents
Interweaving public user profiles on the web
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
Bridge analysis in a Social Internetworking Scenario
Information Sciences: an International Journal
Analyzing user behavior across social sharing environments
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
International Journal of Web Based Communities
CooL-AgentSpeak: Endowing AgentSpeak-DL agents with plan exchange and ontology services
Web Intelligence and Agent Systems
Journal of Information Science
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The Social Web is successfully established and poised for continued growth. Web 2.0 applications such as blogs, bookmarking, music, photo and video sharing systems are among the most popular; and all of them incorporate a social aspect, i.e., users can easily share information with other users. But due to the diversity of these applications -- serving different aims -- the Social Web is ironically divided. Blog users who write about music for example, could possibly benefit from other users registered in other social systems operating within the same domain, such as a social radio station. Although these sites are two different and disconnected systems, offering distinct services to the users, the fact that domains are compatible could benefit users from both systems with interesting and multi-faceted information. In this paper we propose to automatically establish social links between distinct social systems through cross-tagging, i.e., enriching a social system with the tags of other similar social system(s). Since tags are known for increasing the prediction quality of recommender systems (RS), we propose to quantitatively evaluate the extent to which users can benefit from cross-tagging by measuring the impact of different cross-tagging approaches on tag-aware RS for personalized resource recommendations. We conduct experiments in real world data sets and empirically show the effectiveness of our approaches.