FolksoViz: a subsumption-based folksonomy visualization using the Wikipedia

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FolksoViz: a subsumption-based folksonomy visualization using the Wikipedia
Authors: Kangpyo Lee, Hyunwoo Kim, Chungsu Jang, Hyoung-Joo Kim [edit item]
Citation: Journal of KISS: Computing Practices 14 (4): 401-11. 2008 June.
Publication type: Journal article
Peer-reviewed: Yes
Database(s):
DOI: 10.1145/1367497.1367672.
Google Scholar cites: Citations
Link(s): Paper link
Added by Wikilit team: Added on initial load
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FolksoViz: a subsumption-based folksonomy visualization using the Wikipedia is a publication by Kangpyo Lee, Hyunwoo Kim, Chungsu Jang, Hyoung-Joo Kim.


[edit] Abstract

Folksonomy, which is created through the collaborative tagging from many users, is one of the driving factors of Web 2.0. Tags are said to be the web metadata describing a web document. If we are able to find the semantic subsumption relationships between tags created through the collaborative tagging, it can help users understand the metadata more intuitively. In this paper, targeting del.icio.us tag data, we propose a method named {FolksoViz} for deriving subsumption relationships between tags by using Wikipedia texts. For this purpose, we propose a statistical model for deriving subsumption relationships based on the frequency of each tag on the Wikipedia texts, and {TSD} {(Tag} Sense Disambiguation) method for mapping each tag to a corresponding Wikipedia text. The derived subsumption pairs are visualized effectively on the screen. The experiment shows that our proposed algorithm managed to find the correct subsumption pairs with high accuracy.

[edit] Research questions

"In this paper, we propose a technique, called FOlksoViz, for automatically deriving the semantic relations between tags and for visualizing the derived relations on the screen."

Research details

Topics: Other information retrieval topics [edit item]
Domains: Computer science [edit item]
Theory type: Design and action [edit item]
Wikipedia coverage: Sample data [edit item]
Theories: "Undetermined" [edit item]
Research design: Experiment [edit item]
Data source: Experiment responses, Wikipedia pages [edit item]
Collected data time dimension: Cross-sectional [edit item]
Unit of analysis: Article [edit item]
Wikipedia data extraction: Live Wikipedia [edit item]
Wikipedia page type: Article [edit item]
Wikipedia language: Not specified [edit item]

[edit] Conclusion

"FolksoViz managed to display the semantic relations between tags in an effective and intuitiveway to accomplish the folksonomy visualization. We fully exploited the characteristics of Web 2.0: the collaborative tagging in del.icio.us and the collective intelligence in the Wikipedia."

[edit] Comments


Further notes[edit]

Facts about "FolksoViz: a subsumption-based folksonomy visualization using the Wikipedia"RDF feed
AbstractFolksonomy, which is created through the cFolksonomy, which is created through the collaborative tagging from many users, is one of the driving factors of Web 2.0. Tags are said to be the web metadata describing a web document. If we are able to find the semantic subsumption relationships between tags created through the collaborative tagging, it can help users understand the metadata more intuitively. In this paper, targeting del.icio.us tag data, we propose a method named {FolksoViz} for deriving subsumption relationships between tags by using Wikipedia texts. For this purpose, we propose a statistical model for deriving subsumption relationships based on the frequency of each tag on the Wikipedia texts, and {TSD} {(Tag} Sense Disambiguation) method for mapping each tag to a corresponding Wikipedia text. The derived subsumption pairs are visualized effectively on the screen. The experiment shows that our proposed algorithm managed to find the correct subsumption pairs with high accuracy.rect subsumption pairs with high accuracy.
Added by wikilit teamAdded on initial load +
Collected data time dimensionCross-sectional +
ConclusionFolksoViz managed to display the semantic FolksoViz managed to display the semantic relations between tags in an effective and intuitiveway to accomplish the folksonomy visualization. We fully exploited the characteristics of Web 2.0: the collaborative tagging in del.icio.us and the collective intelligence in the Wikipedia. collective intelligence in the Wikipedia.
Data sourceExperiment responses + and Wikipedia pages +
Doi10.1145/1367497.1367672 +
Google scholar urlhttp://scholar.google.com/scholar?ie=UTF-8&q=%22FolksoViz%3A%2Ba%2Bsubsumption-based%2Bfolksonomy%2Bvisualization%2Busing%2Bthe%2BWikipedia%22 +
Has authorKangpyo Lee +, Hyunwoo Kim +, Chungsu Jang + and Hyoung-Joo Kim +
Has domainComputer science +
Has topicOther information retrieval topics +
Issue4 +
MonthJune +
Pages401-11 +
Peer reviewedYes +
Publication typeJournal article +
Published inJournal of KISS: Computing Practices +
Research designExperiment +
Research questionsIn this paper, we propose a technique, called FOlksoViz, for automatically deriving the semantic relations between tags and for visualizing the derived relations on the screen.
Revid10,777 +
TheoriesUndetermined
Theory typeDesign and action +
TitleFolksoViz: a subsumption-based folksonomy visualization using the Wikipedia
Unit of analysisArticle +
Urlhttp://dl.acm.org/citation.cfm?id=1367672 +
Volume14 +
Wikipedia coverageSample data +
Wikipedia data extractionLive Wikipedia +
Wikipedia languageNot specified +
Wikipedia page typeArticle +
Year2008 +