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.
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Tsai, F.S., Chen, Y., Chan, K.L. (2007). Probabilistic Techniques for Corporate Blog Mining. In: Washio, T., et al. Emerging Technologies in Knowledge Discovery and Data Mining. PAKDD 2007. Lecture Notes in Computer Science(), vol 4819. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77018-3_5
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DOI: https://doi.org/10.1007/978-3-540-77018-3_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77016-9
Online ISBN: 978-3-540-77018-3
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