计算机技术与发展2024，Vol.34Issue(4)：30-34,5.DOI:10.20165/j.cnki.ISSN1673-629X.2024.0005
基于相关性模型与大数据分析的关键词优化方法研究
Research on Keyword Optimization Method Based on Correlation Model and Big Data Analysis
摘要
Abstract
With the rapid development of computer networks and information technology,e-commerce has experienced explosive development.E-commerce online store operation has become a technology pursued by a large number of e-commerce practitioners.With the popularization and application of big data technology,e-commerce online store operation technology is also constantly evolving,and keyword selection and optimization based on big data is an important technology that people pay attention to.The correlation model is the basic model for sorting product searches on e-commerce platforms.Search Engine Optimization(SEO)based on the correlation model is currently the basic method for keyword optimization and screening in e-commerce data-driven operations.We combine the original method with big data analysis to optimize and screen keywords from multiple dimensions such as keyword col-lection,screening,combination,monitoring,and exchange,and propose and discuss three optimization models for keyword selection:com-petition coefficient,number of single grade competitions,and adaptability of keyword subject price range.Conduct practical monitoring on the effectiveness of the selected keywords after selection optimization.A large amount of monitoring data shows that using the keyword selection optimization method combining correlation model and big data analysis to obtain product title keywords can effectively improve the exposure of the product click through rate and conversion rate,achieving more efficient online store traffic and transaction volume.关键词
相关性模型/大数据分析/电商运营/关键词优化/点击率Key words
relational model/big data analysis/e-commerce operation/key word optimization/click through rate分类
信息技术与安全科学引用本文复制引用
文继权..基于相关性模型与大数据分析的关键词优化方法研究[J].计算机技术与发展,2024,34(4):30-34,5.基金项目
2020年辽宁省教育科研经费项目(JL202017) （JL202017）
