Target and Swear Word Detection Using Sentence Analysis in Real-Time Chatting

실시간 채팅 환경에서 문장 분석을 이용한 대상자 및 비속어 검출

  • 염충석 (상명대학교 소프트웨어학과) ;
  • 장준영 (상명대학교 소프트웨어학과) ;
  • 장유환 (상명대학교 소프트웨어학과) ;
  • 김현철 (상명대학교 소프트웨어학과) ;
  • 박희민 (상명대학교 소프트웨어학과)
  • Received : 2021.03.12
  • Accepted : 2021.03.17
  • Published : 2021.03.31


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.


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