LAUSR

The construction of regional electronic commerce large data analysis platform is studied. First, the collaborative filtering algorithm is focused on the further elaboration. According to the demand of the recommendation system of the electronic commerce large data analysis platform of a certain agricultural product, the most core part of the recommendation system is realized and the collaborative filtering algorithm is improved emphatically. Based on the large user behavior data accumulated by the regional e-commerce platform, by mining the user’s implicit evaluation of the merchandise, the sparsity of the scoring matrix is reduced, and the recommended effect of the algorithm is improved. The experimental results show that the improved algorithm can improve the efficiency and accuracy of the data processing of the regional electronic Commerce large data analysis platform.