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http://dx.doi.org/10.9717/kmms.2019.22.6.695

Realtime Word Filtering System against Variations of Censored Words in Korean  

Kim, ChanWoo (Department of Computer Science & Engineering, Graduate School, Incheon National University)
Sung, Mee Young (Department of Computer Science & Engineering, Incheon National University)
Publication Information
Journal of Korea Multimedia Society / v.22, no.6, 2019 , pp. 695-705 More about this Journal
Abstract
The level of psychological damage caused by verbal abuse among cyberbully victims is very serious. It is going to introduce a system that determines the level of sanctions against chatting in real time using the automatic prohibited words filtering based on artificial neural network. In this paper, we propose a keyword filtering method that detects the modified prohibited words and determines whether the corresponding chat should be sanctioned in real time, and a real-time chatting screening system using it. The accuracy of filtering through machine learning was improved by processing data in advance through coding techniques that express consonants and vowels of similar pronunciation at close distances. After comparing and analyzing Mahalanobis-based clustering algorithms and artificial neural network-based algorithms, algorithms that utilize artificial neural networks showed high performance. If it is applied to Internet chatting, comments or online games, it is expected that it will be able to filter more effectively than the existing filtering method and that this will ease communication inconvenience due to existing indiscriminate filtering methods.
Keywords
Filtering Vulgar Words; Online Chat Censorship; Korean Encoding; Natural Language Processing; Artificial Neural Network;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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