A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
A guided tour to approximate string matching
ACM Computing Surveys (CSUR)
Integrating Folksonomies with the Semantic Web
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Pattern Matching Techniques to Identify Syntactic Variations of Tags in Folksonomies
WSKS '08 Proceedings of the 1st world summit on The Knowledge Society: Emerging Technologies and Information Systems for the Knowledge Society
Personalized recommendation in social tagging systems using hierarchical clustering
Proceedings of the 2008 ACM conference on Recommender systems
Semantic Grounding of Tag Relatedness in Social Bookmarking Systems
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
The state of the art in tag ontologies: a semantic model for tagging and folksonomies
DCMI '08 Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications
Improving folksonomies quality by syntactic tag variations grouping
Proceedings of the 2009 ACM symposium on Applied Computing
An unsupervised model for exploring hierarchical semantics from social annotations
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
APPECT: an approximate backbone-based clustering algorithm for tags
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
The role of the community in a technical support community: a case study
OCSC'13 Proceedings of the 5th international conference on Online Communities and Social Computing
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Folksonomies have emerged as a common way of annotating and categorizing content using a set of tags that are created and managed in a collaborative way. Tags carry the semantic information within a folksonomy, and provide thus the link to ontologies. The appeal of folksonomies comes from the fact that they require a low effort for creation and maintenance since they are community-generated. However they present important drawbacks regarding their limited navigation and searching capabilities, in contrast with other methods as taxonomies, thesauruses and ontologies. One of these drawbacks is an effect of its flexibility for tagging, producing frequently multiple syntactic variations of a same tag. Similarity measures allow the correct identification of tag variations when tag lengths are greater than five symbols. In this paper we propose the use of cosine relatedness measures in order to cluster tags with lengths lower or equal than five symbols. We build a discriminator based on the combination of a fuzzy similarity and a cosine measures and we analyze the results obtained.