Social trend tracking by time series based social tagging clustering

Shihn Yuarn Chen, Tzu Ting Tseng, Hao Ren Ke, Chuen Tsai Sun

研究成果: 雜誌貢獻文章

7 引文 斯高帕斯(Scopus)

摘要

Social tagging is widely practiced in the Web 2.0 era. Users can annotate useful or interesting Web resources with keywords for future reference. Social tagging also facilitates sharing of Web resources. This study reviews the chronological variation of social tagging data and tracks social trends by clustering tag time series. The data corpus in this study is collected from Hemidemi.com. A tag is represented in a time series form according to its annotating Web pages. Then time series clustering is applied to group tag time series with similar patterns and trends in the same time period. Finally, the similarities between clusters in different time periods are calculated to determine which clusters have similar themes, and the trend variation of a specific tag in different time periods is also analyzed. The evaluation shows the recommendation accuracy of the proposed approach is about 75%. Besides, the case discussion also proves the proposed approach can track the social trends.

原文英語
頁(從 - 到)12807-12817
頁數11
期刊Expert Systems with Applications
38
發行號10
DOIs
出版狀態已發佈 - 2011 九月 15

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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