InFeRno – An Intelligent Framework for Recognizing Pornographic Web Pages
2011; Springer Science+Business Media; Linguagem: Inglês
10.1007/978-3-642-23808-6_46
ISSN1611-3349
AutoresSotiris Karavarsamis, Nikos Ntarmos, Konstantinos Blekas,
Tópico(s)Anomaly Detection Techniques and Applications
ResumoIn this work we present InFeRno, an intelligent web pornography elimination system, classifying web pages based solely on their visual content. The main characteristics of our system include: (i) a powerful vector space with a small but sufficient number of features that manage to improve the discriminative ability of the SVM classifier; (ii) an extra class (bikini) that strengthens the performance of the classifier; (iii) an overall classification scheme that achieves high accuracy at considerably lower runtime costs compared to current state-of-the-art systems; and (iv) a full-fledged implementation of the proposed system capable of being integrated with ICAP-aware web proxy cache servers.
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