Tag quality feedback: a framework for quantitative and qualitative feedback on tags of social web

Authors:
Tae-Gil Noh;Jae-Kul Lee;Seong-Bae Park;Seyoung Park;Sang-Jo Lee;Kweon-Yang Kim
Affiliations:
Department of Computer Engineering, Kyungpook National University, Daegu, Korea;Department of Computer Engineering, Kyungpook National University, Daegu, Korea;Department of Computer Engineering, Kyungpook National University, Daegu, Korea;Department of Computer Engineering, Kyungpook National University, Daegu, Korea;Department of Computer Engineering, Kyungpook National University, Daegu, Korea;School of Computer Engineering, Kyungil University, Gyeongsan, Korea
Venue:
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Year:
2010

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Abstract

A feedback framework is proposed in this paper to assistWeb 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.