云服务平台下考虑用户偏好的设计服务推荐方法

Under the cloud service platform, in order to improve the quality of product design service recommendation and enhance the interaction between users and service providers during the process of product collaborative design, the framework of personalized product design service recommendation was built, and a design service recommendation method for considering user demand preference was developed. Firstly, Fuzzy C-means (FCM) clustering algorithm was adopted to fulfill initial clustering of users. Then, optimizing the function of user similarity and score prediction by improved collaborative filtering method based on user (User-based CF) to increase the accuracy of the target users for predicting scores design service recommendation items. Finally, the update and iteration of product design services could be realized through the interactive feedback of users on design service recommendation results. The design requirement of wall-mounted intelligent air conditioning which submitted by the users in Design Cloud Service Platform was taken as an example to verify the effectiveness of the proposed method.