Haoliang Cui1, Shaozhang Niu1, Keyue Li1,*, Chengjie Shi2, Shuai Shao3, Zhenguang Gao4
Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 277-291, 2021, DOI:10.32604/iasc.2021.016408
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… More >
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