基于N层向量空间模型的信息检索算法

N层向量空间模型在传统向量空间模型的基础上提出了的一种新的信息检索算法模型，这种模型将一篇文档从逻辑上划分为N个相对独立的文本段，然后按照文本段的内容建立文本特征向量以及文本权值向量，在此模型的基础上，更为精确地定义了特征值向量和相似度的计算方法，使之能比较好地适应文档集合的动态扩充，理论分析和实验结果表明，基于此模型实现的信息检索算法具有较快的查找速度和较高的查准率。

AN INFORMATION-RETRIEVAL METHOD BASED ON N-LEVEL VECTOR MODEL

A new information-retrieval algorithm based on the N-level vector model is proposed. The N-level vector model partitions a document into N level text paragraphs. The text feature vectors and the text weight vectors are defined according to the text paragraphs' context. The calculation method of the feature vectors and the similarity are defined much more precisely such that the algorithm can adapt the dynamitic extension of the document set. The theoretic analysis and the experimental results show that the new algorithm has higher precision and faster computation speed.