Concept formation in structured domains
Concept formation knowledge and experience in unsupervised learning
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Communications of the ACM
The anatomy of a large-scale hypertextual Web search engine
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Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
The ant colony optimization meta-heuristic
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UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Evaluating collaborative filtering recommender systems
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Web usage mining based on probabilistic latent semantic analysis
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Exploring social annotations for the semantic web
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HT06, tagging paper, taxonomy, Flickr, academic article, to read
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The Benefit of Using Tag-Based Profiles
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Tag-aware recommender systems by fusion of collaborative filtering algorithms
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Tag recommendations based on tensor dimensionality reduction
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Personalized recommendation in social tagging systems using hierarchical clustering
Proceedings of the 2008 ACM conference on Recommender systems
Exploiting Additional Context for Graph-Based Tag Recommendations in Folksonomy Systems
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Learning optimal ranking with tensor factorization for tag recommendation
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Expert Systems with Applications: An International Journal
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Social tagging systems have grown in popularity over the Web in the last years on account of their simplicity to categorize and retrieve content using open-ended tags. The increasing number of users providing information about themselves through social tagging activities caused the emergence of tag-based profiling approaches, which assume that users expose their preferences for certain contents through tag assignments. Thus, the tagging information can be used to make recommendations. This paper presents an overview of the field of social tagging systems which can be used for extending the capabilities of recommender systems. Various limitations of the current generation of social tagging systems and possible extensions that can provide better recommendation capabilities are also considered.