基于Lucene和LSA的法律咨询系统

本文设计的法律咨询系统，结合法律行业的现状，以中文问答系统为原型，结合了开源数据检索项目Lucene.net，扩展了数据的存储类型. 本文借助中科院研发的中文分词系统，集成到Lucene.Net平台上，弥补了其分词不足. 并使用互信息技术，使同义的法律相关词语优先进行检索. 在中文问答系统的答案提取时，经常出现答案的“漏取”和“错取”的情况，本文提出了一种基于潜在语义分析（LSA）的问题和答案句子相似度计算方法，利用空间向量模型作为表示方法，借助潜在语义分析理论，通过奇异值分解的降维方法构建了一个低维的语义空间，并在语义空间上实现了问题与答案句子相似度计算. 经试验证明，本系统具有较精准的查询正确率以及较少的运行计算时间.

Law Consultation System Based on Lucene and LSA

The designation of this law consultation system, not only considers the situation of the legal profession and based on Chinese Question-Answering System as prototype, but also use searching technology Lucene.net which is a open source project that can preform on many kind of types file. This article also uses ICTCLAS and applies it to the Lucene that makes up for Lucene's lack of word segmentation and mutual information technology to make the law word to be priority search. This paper proposes a method to calculate similarity between question and sentence based on Latent Semantic Analysis (LSA). This method represents the question and sentence with space vector model, under the help of latent semantic analysis theory, and constructs a semantic space, which gets rids of the correlativity between word. And then similarity calculation between question and sentence is implemented in this semantic space. Experiments show that this system has the precision of the operation of the inquiry accuracy and less computation time.