Abstract:In order to solve the problem that traditional methods are not suitable for large-scale user access and poor access accuracy, this paper studies the intelligent access optimization method of user database in cross-border e-commerce system by means of semantic directivity matching and multi-dimensional index tree coding. A cross border electricity supplier database model is established to provide a model basis for database intelligent access. According to fuzzy hierarchical clustering, semantic directivity association features are extracted, semantic directivity similarity calculation is completed in concept lattice, and database intelligent access is realized by similarity matching based on extracted features. Aiming at the problem that it affects the accuracy of access when the user size is large, multi-dimensional index tree coding is used to encoding it. It is optimized to realize the optimization of the intelligent access method of the user database in the cross-border electricity supplier system. The results show that the proposed method can extract the time-domain data and time-frequency data semantic directivity features of cross-border e-commerce system, and can complete the data semantic ontology feature directivity clustering, the redundant interference information is filtered out, and the clustering of feature distribution is strong; the accuracy rate is tested under the condition of high recall rate, and the proposed method is applied to the cross-border e-commerce system. Methods When the recall rate increased, the accuracy rate could be maintained at a higher level, but did not decrease significantly with the increase of recall rate. The accuracy of the proposed method is high.