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Making Folksonomy Machine-Understandable

In: Challenges In Information Technology Management

Author

Listed:
  • PRABODH SHRESTHA

    (Information Systems, University of Maryland, Baltimore County, 1000 Hilltop Circle Baltimore, MD 21250, USA)

  • LEVA ZHOU

    (Information Systems, University of Maryland, Baltimore County, 1000 Hilltop Circle Baltimore, MD 21250, USA)

Abstract

A recent surge of interest in social tagging, also known as folksonomy, challenges the formal and structured knowledge representation in the Semantic Web. Social tagging is attractive in its low barrier to entry and personal and community aspects. However, the benefits of social tagging come at the cost of reduced machine-understandable and reduce effectiveness in information retrieval and organization. To address the above limitations, we propose a framework, UNITAG, to enhance existing social tagging systems with semantic information. It is shown that the framework facilitates information sharing in folksonomy while retaining the usability of folksonomy.

Suggested Citation

  • Prabodh Shrestha & Leva Zhou, 2008. "Making Folksonomy Machine-Understandable," World Scientific Book Chapters, in: Man-Chung Chan & Ronnie Cheung & James N K Liu (ed.), Challenges In Information Technology Management, chapter 13, pages 83-90, World Scientific Publishing Co. Pte. Ltd..
  • Handle: RePEc:wsi:wschap:9789812819079_0013
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