Recognition of Pornographic Web Pages by Classifying Texts and Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Information Processing and Management: an International Journal
Harmful Contents Classification Using the Harmful Word Filtering and SVM
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Intelligent classification of web pages using contextual and visual features
Applied Soft Computing
Recognition of adult images, videos, and web page bags
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) - Special section on ACM multimedia 2010 best paper candidates, and issue on social media
Collaborative blacklist generation via searches-and-clicks
Proceedings of the 20th ACM international conference on Information and knowledge management
Efficient misbehaving user detection in online video chat services
Proceedings of the fifth ACM international conference on Web search and data mining
Mining search intents for collaborative cyberporn filtering
Journal of the American Society for Information Science and Technology
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It is important to protect children and unsuspecting adults from the harmful effects of objectionable materials, such as pornography, violence, and hate messages, which are now prevalent on the World-Wide Web. This calls for effective tools for web content analysis and filtering of objectionable contents. Our study of existing web content filtering systems has identified a number of deficiencies in these systems. Using the analysis of pornographic web pages as a case study, we present an intelligent bilingual web page categorization engine that can determine if an English or Chinese language web page contains pornographic materials. We have implemented the categorization engine to perform offline web page analysis and near-instantaneous online filtering. Performance evaluation of our system has verified its effectiveness.