Web predictive model based on exponential descendent dependency graph
Quan Liu · Jisuanji gongcheng yu sheji · 2010
The predictive accuracy of DG(dependency graph) predictive model is lower,although PPM model has higher predictive accuracy,it occupies large storage space.In order to resolve those problem,the standard DG model is optimized according to Zipf's law and web surfing characteristics,and the EDDG(exponential descendent dependency graph) model is proposed in order to fix the defects which lie in the traditional DG model by exponential descendent algorithms.Experimental results show that the EDDG model can save the storage space while get the similar predictive accuracy with PPM model.