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실시간 채팅 환경에서 문장 분석을 이용한 대상자 및 비속어 검출
염충석,장준영,장유환,김현철,박희민,Yeom, Choongseok,Jang, Junyoung,Jang, Yuhwan,Kim, Hyun-chul,Park, Heemin 한국반도체디스플레이기술학회 2021 반도체디스플레이기술학회지 Vol.20 No.1
By the increase of internet usage, communicating online became an everyday thing. Thereby various people have experienced profanity by anonymous users. Nowadays lots of studies tried to solve this problem using artificial intelligence, but most of the solutions were for non-real time situations. In this paper, we propose a Telegram plugin that detects swear words using word2vec, and an algorithm to find the target of the sentence. We vectorized the input sentence to find connections with other similar words, then inputted the value to the pre-trained CNN (Convolutional Neural Network) model to detect any swears. For target recognition we proposed a sequential algorithm based on KoNLPY.