基于大数据和支持向量机分类法的图书馆中转站构建研究

经济增长,群众的物质需求得到满足后,文化需求就会相对增加,书籍作为重要的文化载体,正在重新被我们拾起。但是在众多场所中,例如社区居民,大型工厂,存在借阅不平衡的问题,大量的图书资源集中在高校图书馆以及市区少量的公共图书馆,无法辐射到大量的有需求群众集体,文章将以大数据为背景,结合支持向量机分类法,以高校图书馆为起点,探讨建立中转借阅体系,以解决图书借阅运营模式相对落后,无法充分利用资源的问题。

Research on the Construction of Library Transfer Station Based on Big Data and Support Vector Machine Classification

When the economic growth and the material needs of the masses are met,the cultural needs will increase relatively,and books,as an important cultural carrier,are being picked up by us again.However,in many places,such as community residents and large factories,there is a problem of unbalanced borrowing.A large number of book resources are concentrated in university libraries and a small number of public libraries in the urban area,and can not radiate to a large number of mass collectives in need.This paper will take big data as the background,combined with support vector machine classification,and take the university library as the starting point,to explore the establishment of a transit lending system in order to solve the relatively backward operation mode of book lending.The problem of not being able to make full use of resources.