• Title/Summary/Keyword: Filtering Vulgar Words

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The Online Game Coined Profanity Filtering System by using Semi-Global Alignment (반 전역 정렬을 이용한 온라인 게임 변형 욕설 필터링 시스템)

  • Yoon, Tai-Jin;Cho, Hwan-Gue
    • The Journal of the Korea Contents Association
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    • v.9 no.12
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    • pp.113-120
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    • 2009
  • Currently the verbal abuse in text message over on-line game is so serious. However we do not have any effective policy or technical tools yet. Till now in order to cope with this problem, the online game service providers have accumulated a set of forbidden words and applied this list on the textual word used in on-line game, which is called 'Swear filter'. But young on-line game players easily avoid this filtering method by coining another words which is not kept in the list. Especially Korean is very easy to make new variations of a vulgar word. In this paper, we propose one smart filtering algorithm to identify newly coined profanities. Important features of our method include the canonical form transformation of coined profanities, semi-global alignment between in the level of consonant and vowel units. For experiment, we have collected more than 1000 newly coined vulgar words in on-line gaming sites and tested these word against our methods. where our system have successfully filtered more than 90% of those newly coined vulgar words.

Realtime Word Filtering System against Variations of Censored Words in Korean (변형된 한글 금칙어에 대한 실시간 필터링 시스템)

  • Kim, ChanWoo;Sung, Mee Young
    • Journal of Korea Multimedia Society
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    • v.22 no.6
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    • pp.695-705
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    • 2019
  • 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.