摘要
提出了一种基于学习的方法,对用户进行隐式的、分布式的建模。学习的作用体现在两个方面:通过基于学习的合同网协议获取用户的原始模型;通过基于观察的学习获得本次登录后用户的新模型。与其他建模方式相比,该方法不限制用户登录的终端又能充分利用用户的历史信息;该方法不侵犯用户的隐私,具有较好的适应性,通过学习,系统可以了解不同用户的爱好以及同一个用户的时变爱好。
A new learning-based user modeling approach is proposed.An implicit,distributed user model can be built by this method.Machine learning is used in two stages.First,learning-based CNP(Contract Network Protocol) is used to get the initial user model.Second,observation-based learning is used to update user model.Compared with other user modeling,this method does not limit the location of user login while it can make full use of user's history information;It dose not violate user's privacy;It possesses dynamic adaptation with respect to preferences of different users,and time-varying preferences of an individual user during a session.
出处
《吉林大学学报(信息科学版)》
CAS
2004年第1期45-48,共4页
Journal of Jilin University(Information Science Edition)
基金
国家自然科学基金资助项目(69973012)