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Web个性化研究的关键技术是推荐系统,其作用是根据用户模型推荐个性化内容,当前推荐技术的研究主要包括四种模式:基于规则过滤、基于内容过滤、基于协作过滤和混合过滤模式。前三种工作模式采用的是传统技术和方法,根据当前推荐系统研究的重点和热点,提出一种Web个性化应用的智能过滤推荐模式。智能过滤推荐模式组合采用以上三种工作模式的优点、避免前三种单一模式的缺点。该方法的突出特点是根据离线学习模型提取的用户偏好特征,实现在线智能推荐。
The key technology of Web personalized research is the recommendation system, whose role is to recommend personalized content according to the user model. The current research on recommended technologies mainly includes four modes: rule-based filtering, content-based filtering, collaborative filtering and hybrid filtering. The first three work modes adopt the traditional techniques and methods. According to the focus and hot points of the current recommendation system research, a smart filtering recommendation mode for Web personalization is proposed. Intelligent filtering recommendation mode combination of the advantages of the above three modes of work to avoid the shortcomings of the first three single mode. The outstanding feature of this method is to realize the online intelligent recommendation based on the user preference features extracted from the offline learning model.