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Automatic Classification of Advertising Restaurant Blogs Using Machine Learning Techniques
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 Title & Authors
Automatic Classification of Advertising Restaurant Blogs Using Machine Learning Techniques
Chang, Jae-Young; Lee, Byung-Jun; Cho, Se-Jin; Han, Da-Hye; Lee, Kyu-Hong;
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 Abstract
Recently, users choosing a restaurant basedon information provided by blogs are increasing significantly. However, those of most blogs are unreliable since domestic restaurant blogs are occupied by advertising postings written by `power bloggers`. Thus, in order to ensure the reliability of blogs, it is necessary to filter the advertising blogs which are sometimes false or exaggerated. In this paper, we propose the method of distinguishing the advertising blogs utilizing an automatic classification technique. In the proposed technique, we first manually collected advertising restaurant blogs, and then analyzed features which are commonly found in those blogs. Using the extracted features, we determined whether a given blog is advertising one applying automatic classification algorithms. Additionally, we select the features and the algorithm which guarantee optimal classification performance through comparative experiments.
 Keywords
advertising blog;review;filtering;machine learning;classification;
 Language
Korean
 Cited by
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