Probabilistic Techniques for Corporate Blog Mining

  • Flora S. Tsai
  • Yun Chen
  • Kap Luk Chan
Conference paper

DOI: 10.1007/978-3-540-77018-3_5

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4819)
Cite this paper as:
Tsai F.S., Chen Y., Chan K.L. (2007) Probabilistic Techniques for Corporate Blog Mining. In: Washio T. et al. (eds) Emerging Technologies in Knowledge Discovery and Data Mining. PAKDD 2007. Lecture Notes in Computer Science, vol 4819. Springer, Berlin, Heidelberg

Abstract

With the proliferation of blogs, or weblogs, in the recent years, information in the blogosphere is becoming increasingly difficult to access and retrieve. Previous studies have focused on analyzing personal blogs, but few have looked at corporate blogs, the numbers of which are dramatically rising. In this paper, we use probabilistic techniques to detect keywords from corporate blogs with respect to certain topics. We then demonstrate how this method can present the blogosphere in terms of topics with measurable keywords, hence tracking popular conversations and topics in the blogosphere. By applying a probabilistic approach, we can improve information retrieval in blog search and keywords detection, and provide an analytical foundation for the future of corporate blog search and mining.

Keywords

Weblog search blog mining probabilistic latent semantic analysis corporate blog business blog web mining 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Flora S. Tsai
    • 1
  • Yun Chen
    • 1
  • Kap Luk Chan
    • 1
  1. 1.School of Electrical & Electronic Engineering, Nanyang Technological University, 639798Singapore

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