The Effect of Co-rating on the Recommender System of User Base

This study is to investigate the effect of the number of co-rated users to the MAE. User based collaborative algorithm generally uses similarity weight to compute the relation of active user and other users. The original estimation algorithm of the GroupLens used the Pearson's correlation coefficient, soon after other researchers used various weighting. The Pearson’s correlation coefficient and Vector similarity, which is used in the field of information retrieval, are commonly used to the estimation algorithm. In prediction, we analyze the effect of the number of co-rated users on the user based recommender system.