Efficient collaborative filter using extreme learning machine
Xin Wang · Jisuanji gongcheng yu sheji · 2011
Collaborative filtering as an effective technique for personalized recommendation has been widely applied in many fields,but with the increase of users and resources,high-dimensionality and scarcity has seriously degrade the recommendation quality and slow down the calculation speed.According to this problem,collaborative filtering based on extreme learning machine has been proposed and implemented.Principal component analysis is used to solve high-dimensional sparse problem,while extreme learning machine is applied to solve the problem of slow speed.Experimental results have shown that the proposed method has good generalization performance and learning speed,and it can meet the demand for personalized recommendation well.