摘要：随着电子商务的快速发展，用户信任度成为影响电子商务发展的重要因素之一。本文基于大数据技术，构建了B2C跨电子商务用户信任度预测模型，并应用于实际电子商务平台中。首先，通过数据挖掘技术，提取了用户信任度的关键特征；然后，采用机器学习算法，构建了用户信任度预测模型；最后，将模型应用于实际电子商务平台中，验证了模型的有效性和实用性。实验结果表明，该模型能够准确预测用户的信任度，为电子商务平台提供了重要的决策支持。
关键词：大数据；B2C跨电子商务；用户信任度；预测模型
Abstract: With the rapid development of e-commerce, user trust has become one of the important factors affecting the development of e-commerce. Based on big data technology, this paper constructs a B2C cross-e-commerce user trust prediction model and applies it to actual e-commerce platforms. First, through data mining technology, the key features of user trust are extracted; then, machine learning algorithms are used to construct a user trust prediction model; finally, the model is applied to actual e-commerce platforms to verify the effectiveness and practicality of the model. The experimental results show that the model can accurately predict user trust, providing important decision support for e-commerce platforms.
Keywords: big data; B2C cross-e-commerce; user trust; prediction model
基于大数据技术的B2C跨电子商务用户信任度预测模型构建及应用
