Smart manufacturing service (SMS)-oriented precise pushing method

Abstract

The invention relates to a smart manufacturing service (SMS)-oriented precise pushing method in the technical field of internet information interaction. The smart manufacturing service (SMS)-orientedprecise pushing method comprises a step 1 and a step 2. The method comprises the following steps of: step 1, calculating the weight of a recommendation standard by using a rough decision test and an evaluation experiment method; and step 2, using a rough collaborative filtering method to complete SMS module recommendation based on multi-criterion decision. According to the smart manufacturing service (SMS)-oriented precise pushing method, the time cost for the user to obtain the target intelligent manufacturing service can be reduced, the possibility of errors caused by manual subjective selection of the intelligent manufacturing service is reduced, and an enterprise is helped to intelligently and actively respond to user requirements. According to the method, the problems of interaction among recommendation standards, importance influence of the recommendation standards, subjectivity of user evaluation and the like are comprehensively considered, and objective distribution of the userevaluation is considered by using the rough number, so that a recommendation result is ensured to be more accurate.

Description

technical field [0001] The present invention relates to the technical field of Internet information interaction, in particular to a precise push method for intelligent manufacturing services. Background technique [0002] Intelligent manufacturing is to realize the intelligence and innovation of the entire manufacturing value chain, and it is a further improvement of the deep integration of informatization and industrialization. Intelligent manufacturing service is a new service model that reflects the characteristics and advantages of intelligent manufacturing, aiming to enhance the core competitiveness and customer satisfaction of manufacturing enterprises. [0003] At present, most of the existing related research focuses on product search, and there are few studies on SMS personalized recommendation. The existing recommendation methods can be roughly divided into two categories: content-based recommendation and collaborative filtering. However, in these studies, there i...

AI Technical Summary

Problems solved by technology

However, this patent application does not solve the problem of reducing the time cost for users to obtain the target SMS, and cannot reduce the possibility of error-prone manual subjective selection. The accuracy of service push is poor, and it cannot help enterprises realize proactive and intelligent prediction and response to user needs.

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