This paper establishes the Taobao shop credit evaluation model in terms of shop information, goods, and services. Using 242 shop's information from Taobao, after two-step clustering method in SPSS and using BP neural network toolbox, the evaluation index as input, clustering results as output, built the BP neural network of 230 data samples for training, getting the BP network which has a faster convergence speed and higher accuracy rate. On this basis, using 12 shops for the simulation of the endingmodel to predict the credit of shops objectively and eventuallyestablishesthe Taobao shop credit evaluation model.
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