摘要
着眼于顾客行为中隐含的大量顾客偏好信息,构建了信息模型。通过对顾客注册、检索、浏览信息的提取,并针对偏好动态性对其进行及时维护,计算出顾客特征向量作为推荐的依据,旨在提高推荐的准确性和及时性。
According to a large number of customer preference information included in their behaviors, the information model is constructed. By the information extraction from customers＇ registration, searching and browsing, and the timely maintenance on the dynamic of preferences, the customer feature vector is calculated as the recommendatory basis for the purpose of improving the accuracy and timeliness of recommendation.
出处
《天津农学院学报》
CAS
2013年第1期37-40,57,共5页
Journal of Tianjin Agricultural University
关键词
电子商务
顾客偏好
信息模型
特征向量
E-commerce
customer preference
information model
feature vector
