Abstract
Nowadays, an increasing number of people review the comments on each item before they will purchase the commodities and services offered by online shopping malls, Internet blogs, or cafés. However, it is somewhat challenging to routinely read trough all of the comments. The purpose of this study is to introduce some methods to classify the positive or negative review pertaining to the blog comments on a movie written in Korean. For this purpose, a variety of algorithms was used to classify the reviews and allow feature-selection by applying the traditional machine learning method for classifying literature.
This research was conducted with the support of ‘Seoul R&BD Program(10581)’.
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Kang, H., Yoo, S.J., Han, D. (2009). Accessing Positive and Negative Online Opinions. In: Stephanidis, C. (eds) Universal Access in Human-Computer Interaction. Applications and Services. UAHCI 2009. Lecture Notes in Computer Science, vol 5616. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02713-0_38
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DOI: https://doi.org/10.1007/978-3-642-02713-0_38
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