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Mining Social Media for Enhancing Personalized Document Clustering

  • Chin-Sheng YangEmail author
  • Pei-Chun Chang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9191)

Abstract

Social media is nowadays an excellent platform for gathering user intelligence for supporting business intelligence applications. Social tagging system (aka. folksonomy) is a critical mechanism for collaboratively creating, organizing and managing the wisdom of crowds. The knowledge gained from social tagging system should be tremendous assets for conducting and improving various business intelligent applications. Consequently, the purpose of this study is to examine the values of folksonomy on an important business intelligent task, namely personalized document management. Specifically, we employ Delicious, a pioneered social bookmarking service, to construct a statistical-based thesaurus which is then applied to support personalized document clustering. According to our empirical evaluation results, social tagging system indeed improve the quality of the statistical-based thesaurus in comparison with that constructed on the basis of a general-purpose search engine in generating personalized document clusters.

Keywords

Social media Business intelligence Social tagging Social bookmarking Personalized document clustering 

Notes

Acknowledgments

This work was supported by the National Science Council of the Republic of China under the grant NSC 100-2410-H-155-013-MY3 and the Ministry of Science and Technology of the Republic of China under the grant MOST 103-2410-H-155-027-MY3.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Information Management, and Innovation Center for Big Data and Digital ConvergenceYuan Ze UniversityChung-LiTaiwan, ROC

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