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- W1966132377 abstract "인터넷에 공개된 수 많은 웹 문서들에는 유익한 정보를 제공하는 웹 문서들뿐만 아니라, 음란 정보와 관련된 불건전한 유해 웹 문서들이 다수 포함되어 있으며, 본 연구에서는 이러한 유해 웹 문서들을 효과적으로 검출할 수 있는 방법을 제안한다. 즉, 유해 웹 문서들의 분석을 통하여 유해 웹 문서 선정을 위한 평가 항목들을 도출하고, 각 평가 항목별 유해 점수 부여를 위한 평가 기준을 제시한다. 그리고, 유해 점수들의 총합이 임계값 이상인 웹 문서를 유해 웹 문서로 검출한다. 본 연구의 결과는 유해 웹 문서들로부터 이용자를 보호하고 인터넷 사용의 안전성을 향상시키는데 기여할 것으로 기대된다. A huge amount of web documents, which are published on the Internet, provide to users not only helpful information but also harmful information such as pornography. In this paper we propose a method to detect the harmful web documents effectively. We first analyze harmful web documents, and extract factors to determine whether a given web document is harmful. Detail criteria are also described to assign a harmfulness score to each factor. Then the harmfulness score of a web document is computed by adding the harmfulness scores of all factors. If the harmfulness score of a web document is greater than a given threshold, the web document is detected as harmful. It is expected that this study could contribute to the protection of users from harmful web documents on the Internet." @default.
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- W1966132377 date "2005-10-01" @default.
- W1966132377 modified "2023-09-26" @default.
- W1966132377 title "Detecting Harmful Web Documents Based on Web Document Analyses" @default.
- W1966132377 doi "https://doi.org/10.3745/kipstd.2005.12d.5.683" @default.
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