摘要
在web信息服务中提供个性化服务时,一项非常重要的任务就是发现用户的兴趣.目前最有效的方法是通过用户的浏览行为发现用户兴趣.本文通过建立线性回归模型对用户兴趣度的计算方法进行改进,然后将用户兴趣度转化为云模型进行表示,并最终生成能准确表示用户兴趣度的新方法,从而使个性化推荐更加有效.
Discovering user interests is a very important task for providing personalized services in information service on Web. An effective approach is to develop user interests degree of user from their browsing behavior. For the sake of final getting user current interests degree well and truly, the calculation method of .user interests degree is improved after building the linear regression model,and then the user current interests degree is formed into cloud model. Therefore,the commendation for personalization is more efficient by the method.
出处
《兰州交通大学学报》
CAS
2009年第1期71-74,共4页
Journal of Lanzhou Jiaotong University
基金
甘肃省自然科学基金(3ZS042-B25-038)
关键词
个性化服务
用户兴趣
线性回归模型
云模型
personalization
user interests
linear regression model
cloud model