Topigraphy: visualization for large-scale tag clouds
Proceedings of the 17th international conference on World Wide Web
Explorations in tag suggestion and query expansion
Proceedings of the 2008 ACM workshop on Search in social media
Exploring Feedback Models in Interactive Tagging
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Hierarchical auto-tagging: organizing Q&A knowledge for everyone
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
A simple word trigger method for social tag suggestion
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Social networking federation: A position paper
Computers and Electrical Engineering
Bringing the associative ability to social tag recommendation
TextGraphs-7 '12 Workshop Proceedings of TextGraphs-7 on Graph-based Methods for Natural Language Processing
Support for Video Hosting Service Users Using Folksonomy and Social Annotation
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Content-Based Semantic Tag Ranking for Recommendation
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Learning topical translation model for microblog hashtag suggestion
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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There are at least three barriers to utilizing blog tags in classification or navigation: 40% of entries are not (from our observations) tagged, there are many orthographic or synonymous tag variations, and not all tags are informative.We propose a method of multi-autotagging, based on k-NN, which is a case-based classijication method. Our method also has the functions of merging tags with the same meaning and identifying informative tags. For realizing these functions, we propose the term weighting method named residual document frequency(RDF); it can score the similarity between tags. Experiments show the effectiveness of our methods. Our autotagging system is generic and can assign tag(s) to any text as well as blog entries although the training data is collected from the blogosophere.