A framework of user model based on Semi-supervised techniques
With the exponential increase of the information resources on the Web, the need to mine useful information in the personalization system has become more and more important. There are several problems in current personalization applications, which can be solved well with our State-of-the-Art user model framework. Active learning strategy is used to obtain more accurate labeled examples as well as semi-supervised machine learning techniques are used to mitigate user human labor. A new profile space which takes contextual information into account can take full advantage of the information in the users transactional histories. The realization of automatic personalization is more simple and efficient.
Xiaojian Ding Yuancheng Li Yinliang Zhao
School of Electronic and Information Engineering, Xian Jiaotong University, Xian, Shaanxi, 710049, P.R.China
国际会议
AiR08，EM2108，SOAIC08，SIOKM08，BIMA08，DKEEE08(2008IEEE国际电子商务工程学术会议)
西安
英文
396-401
2008-10-22（万方平台首次上网日期，不代表论文的发表时间）