HYBRID RECOMMENDATION METHOD AND SYSTEM FOR LARGE SCALE DATA

摘要

PURPOSE: A system and a method of hybrid recommending for high capacity data are provided to shorten a taking time for providing the recommendation result and improve accuracy of the recommendation result by providing a recommendation result by suing reduced data. CONSTITUTION: Similar neighbors having a similar purchase pattern with a target buyer and different neighbors having a different purchase pattern are selected(S110). By referring purchase history of the different neighbors and purchase history of the target buyer, a boundary function is obtained(S120). By referring the boundary function and a purchase history of the similar neighbors, a recommended item is selected(S130). The similar neighbors and different neighbors are selected by a calculation of a Pearson product-moment correlation coefficient.