摘要
根据用户以往网页浏览的隐式反馈信息来推断用户兴趣,给用户推荐感兴趣的网页内容,提出了网页兴趣度度量方法及其在兴趣模型中的应用。根据用户浏览网页时的停留时间和浏览行为,通过量化的兴趣度度量算法评估出用户对网页内容的感兴趣程度,从而建立起用户兴趣模型;在用户浏览网页的过程中,动态地更新用户兴趣;最终根据归纳出的用户兴趣向用户推荐文章。实验证明提出的网页兴趣度度量方法和对应的兴趣模型是可行的。
To find out users＇ interest by analyzing their implicit feedback ot VlSlung w eorage~, a w^ur,-S,- proposed and used in the interest model. Users＇ interest at the content of the webpage＇s is measured by the interest rate metrics ac- cording to reading time and browsing behavior. During the process of users＇ visiting WebFages, users＇ interest model is updated dynamically and used to recommend articles to the users. Experimental results show that the effectiveness of the interest rate metrics and the according interest model is confirmed.
出处
《微型电脑应用》
2012年第6期29-31,共3页
Microcomputer Applications
关键词
兴趣度
用户兴趣模型
向量空间模型
隐式反馈
Interest Rate
User Interest Model
Vector Space Model
Implicit Feedback
