2-Way Text Classification for Harmful Web Documents

The openness of the Web allows any user to access almost any type of information. However, some information, such as adult content, is not appropriate for all users, notably children. Additionally for adults, some contents included in abnormal porn sites can do ordinary people’s mental health harm....

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Bibliographische Detailangaben
Hauptverfasser:	Kim, Youngsoo, Nam, Taekyong, Won, Dongho
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Algorithmics. Computability. Computer arithmetics Applied sciences Artificial intelligence Computer science control theory systems Computer systems and distributed systems. User interface Exact sciences and technology Feature Selection Algorithm High Term Frequency Information systems. Data bases Memory organisation. Data processing Meta Search Engine Pattern Match Algorithm Software Speech and sound recognition and synthesis. Linguistics Theoretical computing User Dictionary
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Beschreibung
Zusammenfassung:	The openness of the Web allows any user to access almost any type of information. However, some information, such as adult content, is not appropriate for all users, notably children. Additionally for adults, some contents included in abnormal porn sites can do ordinary people’s mental health harm. In this paper, we propose an efficient 2-way text filter for blocking harmful web documents and also present a new criterion for clear classification. It filters off 0-grade web texts containing no harmful words using pattern matching with harmful words dictionaries, and classifies 1-grade,2-grade and 3-grade web texts using a machine learning algorithm.
ISSN:	0302-9743 1611-3349
DOI:	10.1007/11751588_57