FolksoViz: A semantic relation-based folksonomy visualization using the Wikipedia corpus
|FolksoViz: A semantic relation-based folksonomy visualization using the Wikipedia corpus|
|Author(s)||Lee K., Kim H., Shin H., Kim H.-J.|
|Published in||10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009|
|Keyword(s)||Collaborative Tagging, Folksonomy, Semantic Relation, Visualization, Web 2.0, Wikipedia (Extra: Collaborative tagging, Folksonomies, Semantic Relation, Semantic relations, Web 2.0, Wikipedia, Artificial intelligence, Computer science, Computer software, Visualization, World Wide Web, Semantics)|
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FolksoViz: A semantic relation-based folksonomy visualization using the Wikipedia corpus is a 2009 conference paper written in English by Lee K., Kim H., Shin H., Kim H.-J. and published in 10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009.
Tagging is one of the most popular services in Web 2.0 and folksonomy is a representation of collaborative tagging. Tag cloud has been the one and only visualization of the folksonomy. The tag cloud, however, provides no information about the relations between tags. In this paper, targeting del.icio.us tag data, we propose a technique, FolksoViz, for automatically deriving semantic relations between tags and for visualizing the tags and their relations. In order to find the equivalence, subsumption, and similarity relations, we apply various rules and models based on the Wikipedia corpus. The derived relations are visualized effectively. The experiment shows that the FolksoViz manages to find the correct semantic relations with high accuracy.
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