海量图书信息快速检索优化管理仿真研究

摘要

进行海量图书信息快速检索管理,可提高图书馆的服务质量.进行海量图书信息快速检索管理需要建立在海量图书检索信息的快速分类的基础上,但是传统方法通过获得检索信息多范畴分类属性的约简集族,计算多范畴检索信息的复合相似度,利用计算的结果对海量图书信息进行快速检索优化管理,但不能对海量图书信息进行有效分类,降低了图书信息快速检索管理的精度.提出改进主成分分析的海量图书信息快速检索优化管理方法.获取各个图书检索信息特征间的的互信息,并定义为评价准则,计算出全部图书检索信息类型的主成分的数量,在对检索信息分类中引入映射表和误分类率阈值,设定对应不同图书检索信息范畴的属性,计算多范畴图书检索分类的误分类率,依据误分类率对分类图书信息进行标引,利用标引的结果对海量图书检索信息进行快速分类,最终实现了海量图书信息快速检索优化管理.仿真结果表明,所提模型可以帮助用户对海量图书信息进行快速检索.%An optimization management method for fast retrieval of mass library information is proposed based on the modified principal component analysis.Firstly,the mutual information among each information features of library retrieval is obtained and defined as evaluation criteria to work out all principal component quantity of retrieval information type.Then the mapping table and threshold value of misclassifieation rate is introduced into retrieval information classification,and the category attribute of different library retrieval information is set.Moreover,the misclassification rate of multi-category library retrieval classification is calculated,and the classification book information is indexed according to the misclassification rate.Finally,the indexed result is used to classify the fast retrieval information of mass library,and the optimization management of fast retrieval is achieved.The simulation results show that the proposed method can help user to retrieve mass library information fast.