B2B Supplier Personalized Recommendation Algorithms Based on the Cloud Similarity

In order to meet the demand of personalized service for supplier selection found on B2B E-business platform, both the measurement method of cloud similarity and item similarity-based data weight are combined efficiently to improve the algorithms ofitem-based collaborative filtering, and the improved algorithm is applied to the supplier recommendation process. Experimental results show that the improved algorithm can solve the problem of data sparsity and consider the change of users interests in some extent, thus , it implements personalized recommendation service and contributes to the enterprise ’s friendship developing with suppliers and production efficiency and competitive power as well.