Information retrieval by constrained spreading activation in semantic networks
Information Processing and Management: an International Journal - Artificial Intelligence and Information Retrieval
Usage patterns of collaborative tagging systems
Journal of Information Science
Tag Recommendations in Folksonomies
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Tag recommendations based on tensor dimensionality reduction
Proceedings of the 2008 ACM conference on Recommender systems
Learning optimal ranking with tensor factorization for tag recommendation
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
The impact of ambiguity and redundancy on tag recommendation in folksonomies
Proceedings of the third ACM conference on Recommender systems
Latent dirichlet allocation for tag recommendation
Proceedings of the third ACM conference on Recommender systems
The impact of resource title on tags in collaborative tagging systems
Proceedings of the 21st ACM conference on Hypertext and hypermedia
Trend detection in folksonomies
SAMT'06 Proceedings of the First international conference on Semantic and Digital Media Technologies
Efficient Tag Recommendation for Real-Life Data
ACM Transactions on Intelligent Systems and Technology (TIST)
Using tag recommendations to homogenize folksonomies in microblogging environments
SocInfo'11 Proceedings of the Third international conference on Social informatics
Utilising document content for tag recommendation in folksonomies
Proceedings of the sixth ACM conference on Recommender systems
Improving tag recommendation using few associations
IDA'12 Proceedings of the 11th international conference on Advances in Intelligent Data Analysis
Folksonomy link prediction based on a tripartite graph for tag recommendation
Journal of Intelligent Information Systems
Recommending tags with a model of human categorization
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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The objective of a tag recommendation system is to propose a set of tags for a resource to ease the tagging process done manually by a user. Tag recommendation is an interesting and well defined research problem. However, while solving it, it is easy to forget about its practical implications. We discuss the practical aspects of tag recommendation and propose a system that successfully addresses the problem of learning in tag recommendation, without sacrificing efficiency. Learning is realized in two aspects: adaptation to newly added posts and parameter tuning. The content of each added post is used to update the resource and user profiles as well as associations between tags. Parameter tuning allows the system to automatically adjust the way tag sources (e.g., content related tags or user profile tags) are combined to match the characteristics of a specific collaborative tagging system. The evaluation on data from three collaborative tagging systems confirmed the importance of both learning methods. Finally, an architecture based on text indexing makes the system efficient enough to serve in real time collaborative tagging systems with number of posts counted in millions, given limited computing resources.