Improved annotation of the blogosphere via autotagging and hierarchical clustering
Proceedings of the 15th international conference on World Wide Web
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Collective Intelligence in Action
Collective Intelligence in Action
Improved Search in Tag-Based Systems
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Analyzing tag distributions in folksonomies for resource classification
KSEM'11 Proceedings of the 5th international conference on Knowledge Science, Engineering and Management
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Tag-based systems are used by millions of web users to tag, save and share items. User-defined tags, however, are so variable in quality that searching on these tags alone is unsatisfactory. One way to improve search in bookmarking systems is by adding more metadata to the user-created tags to enhance tag quality. The additional metadata we have used is based on document content and largely avoids the idiosyncratic and ambiguous terms too often evident in user-created tags. Such an approach adds value by incorporating information about the content of the resource while retaining the original user-created tags. This paper describes how users' tags can be enhanced with metadata automatically extracted from the original document. An experiment comparing search based only on user-created tags with search using an automatically enhanced tag set, demonstrates how incorporating the extra tags can offer significant benefits.