【摘 要】
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Mobile edge computing is trending nowa-days for its computation efficiency and privacy.The rapid development of e-commerce show great inter-est in mobile edge computing due to numerous rise of small and middle-sized enterprises(SMEs) in the in-ternet.This
【机 构】
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School of Business and Management,Shanghai International Studies University,550 Dalian Rd.(W),Hongko
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Mobile edge computing is trending nowa-days for its computation efficiency and privacy.The rapid development of e-commerce show great inter-est in mobile edge computing due to numerous rise of small and middle-sized enterprises(SMEs) in the in-ternet.This paper predicts the overall sales volume of the enterprise through the classic ARIMA model,and notes that the behavior and arrival differences between the new and old customer groups will affect the accu-racy of our forecasts,so we then use Pareto/NBD to explore the repeated purchases of customers at the in-dividual level of the old customer and the SVR model to predict the arrival of new customers,thus helping the enterprise to make layered and accurate market-ing of new and old customers through machine learn-ing.In general,machine learning relies on powerful computation and storage resources,while mobile edge computing typically provides limited computation re-sources locally.Therefore,it is essential to combine machine learning with mobile edge computing to fur-ther promote the proliferation of data analysis among SMEs.
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