本文提出了一种信息检索模型，以自然语言的形式进行检索，得到用户想要得到的内容，进而提高查询的准确性。
This paper provides an information retrieval model, and it retrieves in way of natural language, gets the content what the users want, so it can improve the retrieval precision.
模糊检索能极大提高系统处理非精确信息的能力，因而基于模糊语言的数学模型至关重要。
Fuzzy retrieves can greatly improve the ability to deal with the inaccurate information and math models based on fuzzy languages are indispensable to succes.
在分词技术、索引技术、结构化查询语言技术的基础上，提出了一个基于XML文档数据库的信息检索系统，这一系统模型主要由分词模块、索引模块及查询模块组成。
This paper puts forward an information retrieval system based on XML documents database on the foundation of segmentation technology, index technology and structured query language technology.
而语言模型在信息检索上的优势也被许多研究所证明。
But, the advantage of language model in information retrieval has been proved in many researches.
而统计语言模型和IR相结合后所形成的IR模型的提出，是信息检索模型研究上的重大进展。
The proposition of IR model formed after statistical language model combined with IR has great progress at information retrieval model research area.
因此，在XML信息检索上进行语言模型的研究是很有意义的。
Therefore, research language model for XML information retrieval is very significant.
另外，统计语言模型自从被应用到信息检索领域就被认为是优秀的信息检索模型框架。
In addition, since the statistical language model was applied to the IR area, it has been regarded as a very good IR framework and been widely researched.
另外，统计语言模型自从被应用到信息检索领域就被认为是优秀的信息检索模型框架。
In addition, since the statistical language model was applied to the IR area, it has been regarded as a very good IR framework and been widely researched.
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