DocumentCode
1879427
Title
FolksoViz: A Semantic Relation-Based Folksonomy Visualization Using the Wikipedia Corpus
Author
Lee, Kangpyo ; Kim, Hyunwoo ; Shin, Hyopil ; Kim, Hyoung-Joo
Author_Institution
Seoul Nat. Univ., Seoul, South Korea
fYear
2009
fDate
27-29 May 2009
Firstpage
24
Lastpage
29
Abstract
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.
Keywords
data visualisation; groupware; information analysis; social networking (online); FolksoViz technique; Web 2.0; Wikipedia corpus; collaborative tagging; del.icio.us tag data; equivalence relation; online social bookmarking service; semantic relation-based folksonomy visualization; similarity relation; subsumption relation; tag cloud; Artificial intelligence; Collaboration; Data visualization; History; Intelligent networks; Software engineering; Tag clouds; Tagging; Uniform resource locators; Wikipedia; Collaborative Tagging; Folksonomy; Semantic Relation; Visualization; Web 2.0; Wikipedia;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing, 2009. SNPD '09. 10th ACIS International Conference on
Conference_Location
Daegu
Print_ISBN
978-0-7695-3642-2
Type
conf
DOI
10.1109/SNPD.2009.80
Filename
5286698
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