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- W3140869834 abstract "At present, the research on the classification of e-commerce users is relatively mature, but with the rise of mobile social networks, the combination of social networks and e-commerce networks has become a trend and is developing rapidly. Traditional e-commerce user classification methods are not suitable for social e-commerce users. Therefore, based on the research on traditional e-commerce user classification methods, according to the characteristics of social e-commerce users, we improved data preprocessing and parameter tuning methods, and proposed a clustering method of social e-commerce users based on the K-means++ algorithm. The test on the actual data of social e-commerce users showed that the retention rates of users of various classes are significantly different, which express that the proposed method can classify social e-commerce users accurately." @default.
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- W3140869834 date "2021-01-01" @default.
- W3140869834 modified "2023-10-03" @default.
- W3140869834 title "A K-means++ Based User Classification Method for Social E-commerce" @default.
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- W3140869834 doi "https://doi.org/10.32604/iasc.2021.016408" @default.
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