摘要
针对传统的图书馆资源整合存在的运行效率低、能耗高、共享后数据利用率低等问题,提出一种基于聚类算法的云计算图书馆资源整合共享方法,结合云计算技术,分析了公共图书馆资源信息,对图书馆资源进行冗余数据降维处理,计算公共图书馆资源的离散样本频谱特征,实现图书资源聚类样本的特征提取;以聚类样本特征提取结果计算出样本的部分密度与各个提取样本与其它样本的最小距离,根据整合规则自适应生成图书资源整合中心,确定整合数目,采用聚类算法对整合后的公共图书馆资源进行共享。实验结果证明,所提方法可以快速、精确地完成公共图书馆资源整合共享。
Traditional resource integration method of library has many defects, such as low operation efficiency, large energy consumption, and low data utilization after sharing. In order to overcome the defects, based on clustering algorithm, a sharing method of cloud computing library resource integration is proposed in this article. Integrated with cloud computing technology, resource information of public library was analyzed. Dimension reduction process of redundant data was carried out for the library resource. Spectrum feature of discrete sample of the resource was calculated. Feature extraction of clustering sample of library resource was achieved. Partial density of sample and minimum distance between the extracted sample and other samples were worked out via the extracted result of clustering sample. Integration center of library resource was generated adaptively according to integration rule. Integration number was confirmed. Clustering algorithm was used to share the integrated public library resource. Simulation results show that the method can complete the integration sharing rapidly and precisely.
作者
张兰兰
ZHANG Lan-lan(Library ofjilin Normal University,Siping Jilin 136000,China)
出处
《计算机仿真》
北大核心
2020年第5期416-419,共4页
Computer Simulation
关键词
云计算
自适应
最小距离
频谱特征
Cloud computing
Adaptive
Minimum distance
Spectrum feature
