基于内容和合作模式的信息推荐机制

如何根据用户的兴趣向用户推荐相关信息成为目前研究的热点,本文提出了基于内容和合作模式的信息推荐机制。其基本思想是根据用户所关心的文本内容将用户划分为不同的内容类,同时按照用户的访问模式以及用户评注的一致性,将用户分成不同的合作类。综合考虑其内容类和合作类对于用户评注影响,利用Fisher 判别分析,给出了信息推荐机制,将相关文本推送给用户。此外,随着信息数量的增加和用户的增加,自动调节各项参数,适应系统的变化,同时考虑到系统负荷和响应速度等方面的约束。

The Mechanism for Information Recommendation Based on Content and Collaboration

Internet becomes the important tool and media for knowledge acquisition, and it is the hotspot to recommend the information related to users' interesting. The new mechanism of information recommendation based on content and collaboration is presented in this paper. It divides users into several content classes based on related texts, at the same time, and it also classifies the users into some collaborative classes based on users' annotations. Finally, it considers that both the content classes and collaborative classes can impress on the users' interest, and it applies the discriminating approach to integrate two classes into a similarity formula as a basis of information recommendation. In addition, it can automatically adjust the system parameters to adapt to the outer environment, system load and the responding speed.