《基于Lucene的索引机制的研究及改善》-毕业学术论文（设计）.doc

lw 摘要 在当今时代，随着互联网的高速发展及在社会各行各业的普及化，网络信息正以惊人的速度增长，如何在这些成千上万的网络信息中准确、快速挖掘出有价值的信息已成为一个热门的课题，这是对信息检索技术的一个重大的挑战，是推动信息检索技术发展的一个极好的机遇。面对网络信息的海量现状，各种信息检索技术的应势产生。一个开发源码的能实现全文信息检索引擎框架—Lucene,就是随着这一过程而产生的。其源码的开放性可以很方便地对其进行二次开发，但在具体的开发应用中仍有很多地方需要改进，使其与具体的应用相结合。Lucene 是针对西文的应用开发的一个框架，由于中文与西文的差异，所以要开发一个基于Lucene的全文信息检索系统，还需要在Lucene的基础上添加对中文信息处理。比如对中文分词的中文分词器，分词是进行信息检索的很重的一部分，分词的好坏对检索结果的精度及速度影响是至关重要的。全文信息检索的另一个重要部分——索引。索引是根据被检索的信息建立的，是用户进行信息有哪些信誉好的足球投注网站直接查询的对象，所以索引性能的好坏也关系到检索结果的检全率和检准率。 在对 Lucene各个模块进行了深入研究之后，本文拟对索引建立进行优化，以提高索引的速度。提高有哪些信誉好的足球投注网站引擎的性能的一个关键就是提高索引速度，本文还将介绍中文全文有哪些信誉好的足球投注网站引擎涉及的一些技术，达到在理论上对全文信息检索系统有系统化的了解，为即将进入社会工作做好最好的准备，掌握研究一门技术的基本方法。 关键词：索引 并行索引 Lucene the research of indexing mechanism based on Lucene and to improve Abstract Nowadays with the rapid development of Internet and the popularization of all walks of life in society, network information is increasing at an amazing speed. How to mine the valuable information accurately and rapidly from these tens of thousands of network information has become a hot topic. This is a major challenge to the information retrieval technology, and also an excellent opportunity to promote the development of it. Faced with the present state of massive network information, all kinds of information retrieval technologies emerged as the times required. Lucene, an engine framework for source development and full-text information retrieval, was created with this process. It can be easily made the second development for its open-source. However, there are still many places that need to be improved to combine with the specific applications during the development of Lucene for specific applications. Lucene is a framework aiming at the application development for western languages. Because of the differences between Chinese and western languages, it also needs to add Chinese information processing on the basis of Lucene, in order to develop a Lucene-based full-text information retrieval system. For example, for the Chinese Analyzer of Chinese word segmentation,