基于知识库的客户网购意向预测系统

发布时间：2018-06-05 17:01

本文选题：知识库 + 网购意向预测　；参考：《计算机工程与应用》2016年13期

【摘要】：电子商务网站所产生的海量客户网购行为数据中蕴含着丰富的反映客户网购行为规律的知识。这些知识是进行客户网购意向预测以及在此基础上进一步进行商品推荐的重要依据。基于Hadoop框架构建了"客户购买意向预测系统",实现了利用隐含在交易数据中的知识对正在浏览中的电商客户的购买意向预测。在基于知识图谱技术构建网购客户购买行为知识库的基础上,利用FP-Growth算法和数据统计方法实现了以增量方式从购买者的交易数据中获取反映用户购买规律的知识,并将取得的知识融合到知识库中。系统能够利用存储于知识库中的知识在客户进行网上购物的过程中对其购买意向进行分析和预测,从而达到提高电子商务平台的运营效率,改善客户购物体验的目的。
[Abstract]:The massive customer online shopping behavior data produced by e-commerce website contains rich knowledge that reflects the law of customer online shopping behavior. These knowledge is an important basis for customer shopping intention prediction and further commodity recommendation on this basis. Based on the Hadoop framework, the "customer purchase intention forecasting system" has been constructed. Using the knowledge implied in the transaction data to predict the purchasing intention of the e-commerce customers in the browser. On the basis of constructing the knowledge base of the purchase behavior of the customers on the basis of the knowledge atlas technology, the FP-Growth algorithm and the data statistics method are used to obtain the rules of the buyer's purchase from the buyer's transaction data in an incremental manner. The system can make use of the knowledge stored in the knowledge base to analyze and predict the purchase intention of the customer in the process of shopping online, so as to improve the operation efficiency of the e-commerce platform and improve the customer purchase experience.
【作者单位】：华北理工大学信息工程学院计算机系;
【基金】：河北省科技支撑计划项目(No.15210110D) 唐山市科技支撑计划项目(No.14130233B) 唐山市科技计划项目(No.14130217B)
【分类号】：TP311.13;F724.6

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