摘要
在科技创新理念的指导下,越来越多的新技术和算法应用于高校档案管理。这些出色的硬件技术和算法使高校的档案更加便捷、智能和高效。基于大数据环境,结合当前高校档案管理的实际需求,对智能文件管理系统的建立和文档检索进行了研究。首先,重点讨论了基于复合的Spring-Struts-Hibernate(SSH)框架系统提出的Java EE框架的缺陷,旨在优化SSH的性能并提高其效率;其次,为了解决当前高校中档案爆炸式增长导致的检索效率不足的问题,对蚁群算法进行了创造性地优化,有效地提升了蚁群算法检索高校档案的效率;最后,分析了优化算法的复杂度和检索效率。结果表明,在大数据环境下提出的算法在检索时间和效率两方面都得到了提高。
Under the guidance of the concept of scientific and technological innovation,more and more new technologies and algorithms are applied to university archives management.These outstanding hardware technologies and algorithms make college files more convenient,intelligent and efficient.Based on the big data environment and the actual needs of college archives management,it studies the establishment of an intelligent file management system and document retrieval.Above all,this article focuses on the shortcomings of the Java EE framework based on the composite Spring-Struts-Hibernate(SSH)system architecture,which aims to optimize the capability of it and improve its efficiency.Next,in order to solve the problem of reduced archive retrieval efficiency caused by the increase in the number of archives,this paper uses ant colony optimization algorithm to classify data mining and apply it to the fast retrieval of big data.At last,it analyzes the complexity and retrieval efficiency of the optimization algorithm.The results show that in the big data environment,the algorithm proposed has improved both retrieval time and efficiency.
作者
李欣佳
Li Xinjia(Heilongjiang University Of Chinese Medicine,Harbin 150040,China)
出处
《电子测量技术》
2020年第10期90-94,共5页
Electronic Measurement Technology
关键词
高校档案管理
SSH框架
蚁群算法
大数据检索
university archives management
SSH framework
ant colony algorithm
big data retrieval
