Objective To build capability verification public service platform based on the proposed recommendation algorithm.Methods Using big data and artificial intelligence related technologies,after the preprocessing of the ability verification data over the years,the recommendation algorithm model of the supply and demand matching between the provider and the participant is established and trained.After the training meets the requirements,the recommendation accuracy of the algorithm is verified in the core business process of the ability verification.Further explore the needs of all parties in the field of capability verification,integrate the resources of all parties in the field of capability verification,and build a national public service platform for capability verification by using unified data specification,unified business process and unified business description method.Results By using this algorithm model,the supply and demand matching of the providers and participants in the capability verification service on the platform has a better fit than other platforms without using the algorithm.Conclusion The construction of the public service platform for capability verification based on recommendation algorithm improves the informatization and intelligence level of the capability verification industry,helps to improve the supply and demand relationship of the industry,and to some extent promotes the technical level and service quality of the capability verification providers.
proficiency testingpublic service platformartificial intelligence
NETL
NSTL
万方数据
