Personalized text content filtering based on typical feedbacks
基于典型反馈的个性化文本信息过滤

This paper presented an approach to perform text content filtering based on content-based and collaborative filtering, using the Probability Model. Introducing the idea of Stereotypic inference, it classified the users into different types and built the model for each type. Moreover, the refreshing of the profiles was based on the feedbacks of the model, and the building of the new profiles was based on the typical profiles. In this way, the precision and the recall were improved significantly.