Research on Filtering System of Harmful Information on Network Based on K Nearest Neighbor Algorithm

摘要

It is the difficult issue how to classify information accurately in the network harmful information filtering, while the K Nearest Neighbor(KNN) classification method have been shown to perform well for pattern classification in many domains. This paper presents a method of network harmful information filtering based on KNN, and improves the classification efficiency by eliminating training samples that may cause misclassification. The experiment shows that the improved system's precision and the recall-precision have been enhanced, and classification time-consuming also has the obvious reduction.