基于大数据分析的能源行业电商平台用户行为预测模型研究

Research on user behavior prediction model of energy industry e-commerce platformbased on big data analysis

近年来,大数据技术飞速发展,在各领域的应用范围持续扩大。基于此背景,为了提高电商平台的运营效率,增强用户体验,在竞争激烈的市场中取得竞争优势,文章研究并开发一种基于大数据分析的能源行业电商平台用户行为预测模型。文章明确大规模电商平台用户行为数据的采集思路,通过数据预处理、特征工程和机器学习建模,构建强大的用户行为预测模型。在此基础上,文章利用真实电商平台数据对模型进行验证。结果显示,所提模型在用户行为预测方面表现出色,具有较高的准确率和召回率。

In recent years,big data technology has shown a rapid development trend,and its application scope in various fields continues to expand.Based on this background,in order to improve the operational efficiency of e-commerce platforms,enhance user experience,and gain competitive advantages in the highly competitive market,this paper explores and develops a user behavior prediction model of e-commerce platforms in the energy industry based on big data analysis.Specifically,it collects user behavior data of large-scale e-commerce platforms,and constructs a powerful user behavior prediction model through data preprocessing,feature engineering and machine learning modeling.The model verification results based on real e-commerce platform data show that the model constructed in this paper has excellent performance in user behavior prediction,with high accuracy and recall rate.