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Pacific Rim International Conference on Artificial Intelligence

PRICAI 2010: PRICAI 2010: Trends in Artificial Intelligence pp 637–642Cite as

Tag Quality Feedback: A Framework for Quantitative and Qualitative Feedback on Tags of Social Web

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6230))

Abstract

A feedback framework is proposed in this paper to assist Web 2.0 users’ taggings. A new measure called Estimated Daily Visit is defined and proposed as the measure for tag quality. Quantitative and qualitative feedback methods are also defined with the measure. A prototype has been implemented to show the validity of the framework, and preliminary result shows that the framework can successfully enhance quality of tags on user-generated contents.

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References

  1. Jschke, R., Marinho, L., Hotho, A., Schmidt-Thieme, L., Stumme, G.: Tag Recommendations in Folksonomies. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (2007)

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Kyungpook National University, 702-701, Daegu, Korea

    Tae-Gil Noh, Jae-Kul Lee, Seong-Bae Park, Seyoung Park & Sang-Jo Lee

  2. School of Computer Engineering, Kyungil University, Gyeongsan, 712-701, Korea

    Kweon-Yang Kim

Authors
  1. Tae-Gil Noh
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  2. Jae-Kul Lee
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  3. Seong-Bae Park
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  4. Seyoung Park
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  5. Sang-Jo Lee
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  6. Kweon-Yang Kim
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Editor information

Editors and Affiliations

  1. School of Computer Science and Engineering, Seoul National University, 151-744, Seoul, Korea

    Byoung-Tak Zhang

  2. Department of Computing,, Macquarie University, NSW, Sydney, Australia

    Mehmet A. Orgun

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© 2010 Springer-Verlag Berlin Heidelberg

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Cite this paper

Noh, TG., Lee, JK., Park, SB., Park, S., Lee, SJ., Kim, KY. (2010). Tag Quality Feedback: A Framework for Quantitative and Qualitative Feedback on Tags of Social Web. In: Zhang, BT., Orgun, M.A. (eds) PRICAI 2010: Trends in Artificial Intelligence. PRICAI 2010. Lecture Notes in Computer Science(), vol 6230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15246-7_62

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  • DOI: https://doi.org/10.1007/978-3-642-15246-7_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15245-0

  • Online ISBN: 978-3-642-15246-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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