采用向量空间模型的个性化信息检索方法

Research on Personalized Information Retrieval Method Using Vector Space Model

为了提升检索结果与用户个性化需求的符合程度,依托向量空间模型提出一种新的检索方法.将用户查询关键词和语料库内的文本信息都映射为向量,从而把检索过程转化为向量相似性的比对.在比对过程中,通过关键词权重突出用户个性化需求,通过余弦相似度判断符合程度.实验结果表明:文中方法的检索结果与用户需求的符合程度明显提高.

In order to improve matching degree between the retrieval results and of user′s personalized needs,a new method based on vector space model is proposed in this paper.Maps the user query keywords and the text information in the database to the many vectors,and then transforms the retrieval process to the comparison of the vector similarity.In the process,the user′s personalized needs are highlighted by the keyword weight,and the matching degree is determined by the cosine similarity.Experimental results show that the retrieval results of this method are significantly improved with the user′s requirements.