Wikipedia Turns to Machine Learning for Fraud Detection

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To help offload the work of volunteer human editors tasked with detecting malevolent postings on the open encyclopedia, Wikipedia has turned to open source machine learning code to develop algorithms for differentiating malevolent new posts from legitimate ones. The goal of the Objective Revision Evaluation Service (ORES) is to help Wikipedia provide a more friendly environment for well-intentioned editors by relaxing current stringent editing restrictions. By identifying obvious vandals, ORES has allowed a positive modification in Wikipedia’s policies toward screening “normal” human editors.

Read more at Wired Magazine


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