摘要：随着跨境电子商务的快速发展，消费者行为转化模型成为了研究的热点。本文基于大数据技术，构建了B2C跨境电子商务消费者行为转化模型，并应用于实际案例中。首先，通过数据挖掘技术对消费者行为数据进行分析，得出了消费者行为转化的关键因素。然后，利用逻辑回归模型对消费者行为进行预测，并通过AUC值评估模型的准确性。最后，将模型应用于实际案例中，实现了对消费者行为的精准预测和个性化推荐。
关键词：大数据；B2C跨境电子商务；消费者行为转化模型；逻辑回归；AUC值
Abstract: With the rapid development of cross-border e-commerce, consumer behavior conversion model has become a hot research topic. Based on big data technology, this paper constructs a B2C cross-border e-commerce consumer behavior conversion model and applies it to practical cases. Firstly, through data mining technology, the key factors of consumer behavior conversion are analyzed. Then, the logistic regression model is used to predict consumer behavior, and the accuracy of the model is evaluated by AUC value. Finally, the model is applied to practical cases to achieve accurate prediction of consumer behavior and personalized recommendation.
Keywords: big data; B2C cross-border e-commerce; consumer behavior conversion model; logistic regression; AUC value
基于大数据技术的B2C跨境电子商务消费者行为转化模型构建及应用
