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Automatic Categorization of Reviews and Opinions of Internet: E-Shopping Customers
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Author(s): Jan Žižka (Mendel University in Brno, Czech Republic)and Vadim Rukavitsyn (Mendel University in Brno, Czech Republic)
Copyright: 2011
Volume: 1
Issue: 2
Pages: 10
Source title:
International Journal of Online Marketing (IJOM)
Editor(s)-in-Chief: Hatem El-Gohary (College of Business & Economics, Qatar University, Qatar)
DOI: 10.4018/ijom.2011040105
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Abstract
E-shopping customers, blog authors, reviewers, and other web contributors can express their opinions of a purchased item, film, book, and so forth. Typically, various opinions are centered around one topic (e.g., a commodity, film, etc.). From the Business Intelligence viewpoint, such entries are very valuable; however, they are difficult to automatically process because they are in a natural language. Human beings can distinguish the various opinions. Because of the very large data volumes, could a machine do the same? The suggested method uses the machine-learning (ML) based approach to this classification problem, demonstrating via real-world data that a machine can learn from examples relatively well. The classification accuracy is better than 70%; it is not perfect because of typical problems associated with processing unstructured textual items in natural languages. The data characteristics and experimental results are shown.
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