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The Study on Implementation of Crime Terms Classification System for Crime Issues Response

첫 페이지 보기
  • 발행기관
    국제문화기술진흥원 바로가기
  • 간행물
    International Journal of Advanced Culture Technology(IJACT) KCI 등재 바로가기
  • 통권
    Volume 8 Number 3 (2020.09)바로가기
  • 페이지
    pp.61-72
  • 저자
    Inkyu Jeong, Cheolhee Yoon, Jang Mook Kang
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A382632

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원문정보

초록

영어
The fear of crime, discussed in the early 1960s in the United States, is a psychological response, such as anxiety or concern about crime, the potential victim of a crime. These anxiety factors lead to the burden of the individual in securing the psychological stability and indirect costs of the crime against the society. Fear of crime is not a good thing, and it is a part that needs to be adjusted so that it cannot be exaggerated and distorted by the policy together with the crime coping and resolution. This is because fear of crime has as much harm as damage caused by criminal act. Eric Pawson has argued that the popular impression of violent crime is not formed because of media reports, but by official statistics. Therefore, the police should watch and analyze news related to fear of crime to reduce the social cost of fear of crime and prepare a preemptive response policy before the people have ‘fear of crime’. In this paper, we propose a deep - based news classification system that helps police cope with crimes related to crimes reported in the media efficiently and quickly and precisely. The goal is to establish a system that can quickly identify changes in security issues that are rapidly increasing by categorizing news related to crime among news articles. To construct the system, crime data was learned so that news could be classified according to the type of crime. Deep learning was applied by using Google tensor flow. In the future, it is necessary to continue research on the importance of keyword according to early detection of issues that are rapidly increasing by crime type and the power of the press, and it is also necessary to constantly supplement crime related corpus.

목차

Abstract
1. Introduction
2. System Flow and Pseudo Code
3. Verification
4. Classification Result
5. Conclusion
Reference

키워드

Multi-Layer Perceptron Crime Machine Learning Classification NLP

저자

  • Inkyu Jeong [ Researcher, Police Science Institute, Asan., Korea ]
  • Cheolhee Yoon [ Researcher, Police Science Institute, Asan., Korea ]
  • Jang Mook Kang [ Professor, Depart of AI Convergence, Global Cyber Univ., Korea ] Corresponding Author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    국제문화기술진흥원 [The International Promotion Agency of Culture Technology]
  • 설립연도
    2009
  • 분야
    공학>공학일반
  • 소개
    본 진흥원은 문화기술(Culture Technology) 관련 산·학·연·관으로 구성된 비영리 단체이다. 문화기술(CT)은 정보통신기술(ICT), 문화적 사고 기반의 예술, 인문학, 디자인, 사회과학기술이 접목된 신융합기술(New Convergence Technology, NCT)로 정의한다. 인간의 삶의 질을 향상시키고, 진보된 방향으로 변화시키고, 문화기술 관련 분야의 학술 및 기술의 발전과 진흥에 공헌하기 위하여, 제3조의 필요한 사업을 행함을 그 목적으로 한다.

간행물

  • 간행물명
    International Journal of Advanced Culture Technology(IJACT)
  • 간기
    계간
  • pISSN
    2288-7202
  • eISSN
    2288-7318
  • 수록기간
    2013~2025
  • 등재여부
    KCI 등재
  • 십진분류
    KDC 600 DDC 700

이 권호 내 다른 논문 / International Journal of Advanced Culture Technology(IJACT) Volume 8 Number 3

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