Fast and effective text mining using linear-time document clustering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Clustering by committee
Introduction to Information Retrieval
Introduction to Information Retrieval
Integrating Folksonomies with the Semantic Web
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Analysis of the Publication Sharing Behaviour in BibSonomy
ICCS '07 Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart 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
Semantic Grounding of Tag Relatedness in Social Bookmarking Systems
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Evaluating similarity measures for emergent semantics of social tagging
Proceedings of the 18th international conference on World wide web
Contextualising tags in collaborative tagging systems
Proceedings of the 20th ACM conference on Hypertext and hypermedia
Searching and Browsing Tag Spaces Using the Semantic Tag Clustering Search Framework
ICSC '10 Proceedings of the 2010 IEEE Fourth International Conference on Semantic Computing
Ontologies are us: a unified model of social networks and semantics
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Scaling pair-wise similarity-based algorithms in tagging spaces
ICWE'12 Proceedings of the 12th international conference on Web Engineering
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Due to the increasing popularity of tagging, it is important to overcome challenges resulting from the free nature of tagging, such as the use of synonyms, homonyms, syntactic variations, etc. The Semantic Tag Clustering Search (STCS) framework deals with these challenges by detecting syntactic variations of tags and by clustering semantically related tags. We evaluate our framework using Flickr data from 2009 and compare the STCS framework to two previously introduced tag clustering techniques. We conclude that our framework performs significantly better in terms of cluster precision compared to one method and has a better average precision compared to the other method.