摘要
用智能Agent实现比较购物要解决海量信息搜索、根据用户偏好进行个性化筛选、用户偏好学习等问题。通过事先把主要电子商务网站的内容下载保存到本地数据库来实现快速搜索,通过关键向量信息过滤法可以实现筛选,通过样本学习和反馈学习可以获取用户偏好。以此实现用智能Agent来替用户比较、搜索合适的商品,从而大大提高在线购物的范围和效率,实现个性化的导购。
To implement comparison shopping by intelligent Agent, there are three problems to be treated： to search in mass information, personal filter according to user bias, user bias learning. Quick search is implemented by downloading and storing the content of main e-Commerce webs in local database beforehand. Information filter is implemented using key vector model in information filter. And customer bias is acquired by samples learning and feedback learning. It is implemented by these means to search fit goods for users by Agent, consequently the range of comparison shopping can be greatly extended and the efficiency can be greatly improved, and personal shopping guide is implemented.
出处
《计算机工程与设计》
CSCD
北大核心
2005年第11期3149-3151,共3页
Computer Engineering and Design
关键词
比较购物
电子商务
AGENT
用户偏好
评价筛选
omparison shopping
electronic commerce
agent
customer bias
evaluation filter
