Parallel recognition of illegal Web pages based on improved KNN classification algorithm

Abstract

There are many illegal Web pages on the Internet,which may have pornographic,violent,gambling or reactionary content. Without being filtered effectively,they will exercise a malign influence on the searching services. An improved K-Nearest Neighbors(KNN) classification algorithm to promote the recognition accuracy was proposed and implemented on a virtualized platform following the MapReduce model provided by the open source software Hadoop,which made it distributed and parallel. Through experiments and comparison with the existing work,it is proved that the proposed recognition method improves the accuracy and efficiency greatly.