摘要： 随着网络信息的迅猛发展，信息检索已经成为人们获取信息不可缺少的工具。基于向量空间模型的检索方法是语义检索的重要研究方向，潜在语义标引模型是向量检索方法的一个有力扩展。对LSI中所涉及的关键技术，包括传统的向量空间模型的原理，以及潜在语义索引模型的原理、设计、实现，进行了研究和探讨，同时开发了一个适合中文信息检索的系统原型。对系统进行了测试，取得了较好的实验效果。

关键词: 潜在语义标引, 向量空间模型, 信息检索, 中文

Abstract: As Internet information has been exploding, information retrieval has facilitated getting knowledge to the people. The approach based on the vector space is the important research direction on information semantic retrieval. Latent semantic indexing(LSI) is an important development for vector space model. The author has done research on how to use LSI technique to develop an application which is proved to perform well in experiment for Chinese information retrieval. The author illustrates some results of experiment.

Key words: Latent semantic indexing(LSI), Vector space model, Information retrieval, Chinese