摘要
电商行业的飞速发展使得用户行为数据规模爆炸式增长,传统的IT架构模式已无法满足持续增长的数据处理需求。针对海量数据处理问题,提出一种基于Hadoop平台的电商用户行为分析模型,通过对Hadoop平台相关技术的研究,设计了包含数据采集、处理、分析及可视化一整套流程的电商用户行为分析系统,并对系统进行功能实现。最后,对该系统进行实际场景测试,结果表明,该系统能够根据不同分析需求快速得到目标数据,实现对用户行为的深度分析与挖掘,为企业调整营销策略,实现精准营销提供数据支撑。
With the rapid development of e-commerce industry, the data of user behavior is developing as a speed of explosion, the traditional IT architecture model has been unable to meet the ever-increasing demand for data processing. Aiming at the problem of massive data processing, an e-commerce user behavior analysis model based on the Hadoop platform is proposed.Through the research on the related technologies of the Hadoop platform, an e-commerce user behavior analysis system including data collection, processing, analysis and visualization is designed, and the system is implemented. Finally, the actual scene test of the system shows that the system can quickly obtain target data according to different analysis needs, realize in-depth analysis and mining of user behavior, and provide data support for enterprises to adjust marketing strategies and achieve precision marketing.
作者
陈伟
CHEN Wei(Department of Computer and Information,Suzhou Vocational and Technical Collge,Suzhou Anhui 234101,China)
出处
《宿州教育学院学报》
2021年第3期120-125,共6页
Journal of Suzhou Education Institute
基金
安徽省高校优秀青年骨干国内访学研修项目(gxgnfx2020152)
安徽省高校自然科学研究重点项目“基于Spark的电商网站用户行为分析预测系统研究”(KJ2019A1058)
安徽省教育厅质量工程项目“OpenStack云平台部署虚拟仿真实训中心”(2019xfzx06),“网站开发与网页设计教学团队”(2018jxtd051),“基于学生画像的精准教学模式生成路径研究与实践”(2020jyxm2226)
