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http://dx.doi.org/10.5573/ieie.2015.52.11.047

Improved Feature Extraction Method for the Contents Polluter Detection in Social Networking Service  

Han, Jin Seop (Department of Computer Science, Kwangwoon University)
Park, Byung Joon (Department of Computer Science, Kwangwoon University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.52, no.11, 2015 , pp. 47-54 More about this Journal
Abstract
The number of users of SNS such as Twitter and Facebook increases due to the development of internet and the spread of supply of mobile devices such as smart phone. Moreover, there are also an increasing number of content pollution problems that pollute SNS by posting a product advertisement, defamatory comment and adult contents, and so on. This paper proposes an improved method of extracting the feature of content polluter for detecting a content polluter in SNS. In particular, this paper presents a method of extracting the feature of content polluter on the basis of incremental approach that considers only increment in data, not batch processing system of entire data in order to efficiently extract the feature value of new user data at the stage of predicting and classifying a content polluter. And it comparatively assesses whether the proposed method maintains classification accuracy and improves time efficiency in comparison with batch processing method through experiment.
Keywords
SNS;
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