摘要
为解决传统PIT图书馆学术数据检索方法存在索引定位数组数量有限、检索承载额度较低等弊端,设计新型图书馆海量网络学术数据的关联检索技术模型。通过定义数据包类型的方式,判断网络学术数据的衍生结构、设置准确的数据命名机制,完成图书馆海量网络学术数据的结构分析。在此基础上,利用关联数据节点的空间编码,确定严格的检索分级法则、完善数据的关联检索流程,实现新型技术模型的搭建,完成图书馆海量网络学术数据的关联检索技术研究。对比模型应用结果可知,与传统PIT检索方法相比,应用新型关联检索技术模型后,索引定位数组数量提升至5.0×10^11TB以上,检索承载额度也达到预期水平。
The traditional PIT library′s academic data retrieval method has some disadvantages,such as the limited number of index positioning arrays and low retrieval load quota.Therefore,a new association retrieval technology model of library′s massive network academic data is designed.By defining the data packet type,the derivative structure of network academic data is judged,and the accurate data naming mechanism is set up to complete the structure analysis of library′s massive network academic data.On this basis,the spatial coding of the associated data nodes is used to determine the strict retrieval grading rules,improve the process of data association retrieval,realize the construction of new technical model,and complete the association retrieval technology research of library′s massive network academic data.The model application results show that,in comparison with the traditional PIT retrieval method,the number of index positioning arrays obtained by the proposed method can reach up to more than 5.0×10^11 TB,and the retrieval load quota can reach the expected level.
作者
张文晶
ZHANG Wenjing(Harbin University of Science and Technology,Harbin 150040,China)
出处
《现代电子技术》
北大核心
2019年第11期181-186,共6页
Modern Electronics Technique
关键词
网络数据
关联检索
数据包定义
衍生结构
命名机制
空间编码
分级法则
技术模型
network data
association retrieval
data packet definition
derivative structure
naming mechanism
spatial coding
hierarchical rule
technical model
