document: Neural networks for web content filtering With the proliferation of harmful Internet content such as pornography , violence , and hate messages , effective content-filtering systems are essential . Many Web-filtering systems are commercially available , and potential users can download trial versions from the Internet . However , the techniques these systems use are insufficiently accurate and do not adapt well to the ever-changing Web . To solve this problem , we propose using artificial neural networks to classify Web pages during content filtering . We focus on blocking pornography because it is among the most prolific and harmful Web content . However , our general framework is adaptable for filtering other objectionable Web material
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