Bringing order to the Web: automatically categorizing search results
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Tag-aware recommender systems by fusion of collaborative filtering algorithms
Proceedings of the 2008 ACM symposium on Applied computing
Tag-based social interest discovery
Proceedings of the 17th international conference on World Wide Web
Tag Recommendations in Folksonomies
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Co-Clustering Tags and Social Data Sources
WAIM '08 Proceedings of the 2008 The Ninth International Conference on Web-Age Information Management
Personalized recommendation in social tagging systems using hierarchical clustering
Proceedings of the 2008 ACM conference on Recommender systems
Extracting data records from the web using tag path clustering
Proceedings of the 18th international conference on World wide web
A Tag Clustering Method to Deal with Syntactic Variations on Collaborative Social Networks
ICWE '9 Proceedings of the 9th International Conference on Web Engineering
RATC: A Robust Automated Tag Clustering Technique
EC-Web 2009 Proceedings of the 10th International Conference on E-Commerce and Web Technologies
Core-Tag Clustering for Web 2.0 Based on Multi-similarity Measurements
Advances in Web and Network Technologies, and Information Management
A Parametric Architecture for Tags Clustering in Folksonomic Search Engines
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
Document recommendation in social tagging services
Proceedings of the 19th international conference on World wide web
Of mice and terms: clustering algorithms on ambiguous terms in folksonomies
Proceedings of the 2010 ACM Symposium on Applied Computing
Extending a hybrid tag-based recommender system with personalization
Proceedings of the 2010 ACM Symposium on Applied Computing
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
A local information passing clustering algorithm for tagging systems
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications
Ontologies are us: a unified model of social networks and semantics
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
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In social annotation systems, users label digital resources by using tags which are freely chosen textual descriptions. Tags are used to index, annotate and retrieve resource as an additional metadata of resource. Poor retrieval performance remains a major problem of most social tagging systems resulting from the severe difficulty of ambiguity, redundancy and less semantic nature of tags. Clustering method is a useful tool to address the aforementioned difficulties. Most of the researches on tag clustering are directly using traditional clustering algorithms such as K-means or Hierarchical Agglomerative Clustering on tagging data, which possess the inherent drawbacks, such as the sensitivity of initialization. In this paper, we instead make use of the approximate backbone of tag clustering results to find out better tag clusters. In particular, we propose an APProximate backbonE-based Clustering algorithm for Tags (APPECT).The main steps of APPECT are: (1) we execute the K-means algorithm on a tag similarity matrix for M times and collect a set of tag clustering results Z =C 1,C 2,...,C m ; (2) we form the approximate backbone of Z by executing a greedy search; (3) we fix the approximate backbone as the initial tag clustering result and then assign the rest tags into the corresponding clusters based on the similarity. Experimental results on three real world datasets namely MedWorm, MovieLens and Dmoz demonstrate the effectiveness and the superiority of the proposed method against the traditional approaches.