摘要
针对当前顾客行为预测主要集中在单个顾客,尚未考虑顾客群体的影响,提出了采用马尔可夫链模型。通过结合顾客的访问日志数据和网站后台记录的交易数据确保预测数据的完整性和真实性,这样能够更准确的预测顾客未来的访问状态,然后求得商品在该时间段的访问情况,以此电子商店经营者可以采取相应的对策来优化商品达到网站效益的最大化。通过实例应用表明,预测结果与实际情况吻合较好,对提高电子商店的效益具有很重要的实用价值。
In view that the researches mostly are focused on individual customer＇s behavior at present, the effect of the whole customers has not been considered to improve the website＇s benefit. The circle are considered use the Markov chain model, through combining the customer＇s web log and transaction data which can ensure the integrity and reality of the predict data, thus more accurately can be forecasted the customer＇s behavior state in the future. Then, we will work out the good＇s visiting state and take appropriate measures to optimize the goods to make the website＇s value maximize. The result of experimentation shows that the result is feasible and reliable, so it can make contributions to e-store.
出处
《计算机工程与设计》
CSCD
北大核心
2009年第4期906-908,共3页
Computer Engineering and Design
基金
北京市教委科技发展计划基金项目(KM200610028015)
