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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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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.
advertising blog;review;filtering;machine learning;classification;
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J. Kim and Y. Kim, How the characteristics of the food-blog marketing effect to purchasing intension with the mediation effect of trust, tourism review, Vol. 30, No. 5, pp. 85-105, 2015.

J. Kim, H. Kim, S. Park, Study on Blog users' Response to Blog Marketing, information Systems Review, Vol. 11, No. 3, pp.1-17, 2009.

E. Blanzieri and A. Bryl, A survey of learning-based techniques of email spam filtering, Artificial Intelligence Review, vol. 29, no. 1, pp. 63-92, 2008. crossref(new window)

G. Cormack, Email Spam Filtering: A Systematic Review, Foundations and Trends in Information Retrieval, vol. 1, no. 4, pp. 335-455, 2007.

I. Park, H. Kang, S. Yoo, Classification of Advertising Spam Reviews, Proceedings of the 22th Annual Conference on Human and Cognitive Language Technology, 2010.

H. An and B. Park, Extracting similar advertising review for Opinion Mining, IEEK Conference 2014, pp.1593-1596, 2014.

N. Jindal and B. Liu, Opinion Spam and Analysis, Proceedings of WSDM, pp. 219-229, 2008.

I. Oh, Pattern Recognition, KyoboBooks, 2008.

J. Chang, and I. Kim, An Experimental Evaluation of Short Opinion Document Classification Using A Word Pattern Frequency, Journal of the Institute of Internet, Broadcasting and Communication, Vol. 12, No. 5, 2012.



A. Mukherjee, V. Venkataraman, B Liu and NS Glance, What Yelp Fake Review Filter Might Be Doing?, Proceedings of International AAAI Conference on Web and Social Media, 2013.

M. Seo. Practical Data Processing and Analysis Using R, GilBut, 2014.

J. Shim, and H. C. Lee, The Development of Automatic Ontology Generation System Using Extended Search Keywords, Journal of the Korea Academia-Industrial cooperation Society, Vol. 11, No. 6, 2009.