摘要
随着互联网上的信息的迅速增长,协作过滤技术得到越来越广泛的应用。结合了显式和隐式计算兴趣度的方法,提出了一种新的计算用户兴趣度的方法。并在此基础上论述了基于兴趣度的协作过滤技术。该方法通过寻找相似用户群体,由相似用户群体来预测用户对某一WEB事务的喜好,并给出了相应的实现算法。实验结果表明,该方法能提供较好的协作推荐服务。
As the rapidly growing of information on Internet, collaborative filtering techniques have been more and more widely applied. Combines explicit and implicit computer users＇ degree of interest method together, putting forward a new method for user interest computing. And analyse the collaborative filtering technology based on the degree of interest. This method proves to find similar users group which can be used to expect the users＇ likes to a certain WEB item , this provides the relevant calculation method . Experiment result makes shown that this method can provide a better collaborative filtering reconarnendation service.
出处
《计算机技术与发展》
2008年第1期106-110,共5页
Computer Technology and Development
基金
安徽省自然科学基金资助项目(KJ2007B245)
