A self-feedback synthesis method for spam filtering
Junlin Zhou · Caai Transactions on Intelligent Systems · 2010
A self-feedback based spam filtering method has been developed.In the construction of the log analysis module,the filtering system was implemented in a way that permited self-feedback when updating filtering rules.Self-analysis,self-decision,and self-optimization were all incorporated.In this way minimal human intervention was required.In traditional massive information filtering,human involvement was very high,leaving filtering accuracy and efficiency highly dependent on the skills of the human operator.Experiments proved that this method overcomes these shortcomings,greatly enhancing the speed and accuracy of information filtering and effectively automating information filtering.