潜在语义索引在飞机故障案例检索的中应用

【作者】 宗士强；

【导师】 顾宏斌；

【作者基本信息】 南京航空航天大学 ， 计算机软件与理论， 2003， 硕士

【摘要】 航空公司希望能根据飞机的故障描述检索故障案例数据库，即给出与输入的故障描述类似的故障案例来指导飞机的故障隔离。 本文在介绍了潜在语义索引模型基本原理的基础上，详细地讨论了如何将该模型应用到飞机的故障案例检索系统中。在对故障案例进行预处理时，本文针对信息检索的特点提出了基于n-元的统计标引法对故障案例进行自动标引。本文以系统的检索性能为依据通过大量的实验确定了潜在语义索引模型所使用的权值方案、K值、相似度阈值等参数。 根据实验的结果，本文设计开发了故障案例检索系统，并对系统进行了优化。更多还原

【Abstract】 Latent semantic indexing (LSI) is a completely automatic yet intelligent indexing method,widely applicable,and a promising way to improve user’ s access of many kinds of textual materials. LSI tries to overcome the problem of lexical matching by using statistically derived conceptual indices instead of individual words for retrieval.In this thesis LSI is introduced into case retrieval,and the application of LSI represented also. In order to preprocess the text of aircraft fault,a new automatic indexing method based on n-gram is proposed. Large quantities of experiments to adjust the parameters of LSI model are done so that the performance of case retrieval system is excellent.An LSI-based case retrieval system is developed and some work is done to optimize the system.更多还原