Abstract
Identification of a blogger’s interest is usually solved as a classification problem of a sequence of his/her blog entries. In constructing a blog entry classifier, we need as training data a rather large set of blog entries that are manually labeled with a class label. In contrast, we can easily obtain a set of blog sites with class labels. In this paper, we present a method for constructing a blog entry classifier using only a set of blog sites with class labels. Our method is based on the Naive Bayes classifier coupled with the EM algorithm.
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Hagiwara, K., Takamura, H., Okumura, M. (2010). Constructing Blog Entry Classifiers Using Blog-Level Topic Labels. In: Cheng, PJ., Kan, MY., Lam, W., Nakov, P. (eds) Information Retrieval Technology. AIRS 2010. Lecture Notes in Computer Science, vol 6458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17187-1_35
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DOI: https://doi.org/10.1007/978-3-642-17187-1_35
Publisher Name: Springer, Berlin, Heidelberg
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