基于VSM的个性化信息过滤算法的研究

Research of personalized information filtering algorithm based on VSM

针对当前搜索引擎"所有用户,同一结果"模式的不足,分析了用户兴趣模型与文档的权值特征,在研究基于向量夹角余弦相关度排序算法的基础上,引入重要度因子,结合文档结构、查询请求及用户兴趣模型等信息,提出了一种基于VSM的个性化信息过滤算法,以实现个性化检索的目的,提高检索系统的查准率。

According to some weaknesses of ＂all users, the same results＂ in today＇s information retrieval, the paper analyzes the user interest profile and the document＇s weight feature. On the base of the study of the correlativity ranking algorithm based on vector angle cosine, it introduces the importance factor, and combines with the structure of the document, the query request and user interest model information,a new kind of personalized information filtering algorithm is proposed in this paper, which aims to realize personalized information retrieval and improves the system precision.