Information retrieval algorithm of industrial cluster based on vector space

被引:0
|
作者
Li, Rongsheng [1 ]
Hassan, Nasruddin [2 ]
机构
[1] Northwest Univ, Sch Econ & Management, Xian 710127, Shaanxi, Peoples R China
[2] Univ Kebangsaan Malaysia, Sch Math Sci, Fac Sci & Technol, Bangi, Selangor, Malaysia
来源
OPEN PHYSICS | 2019年 / 17卷 / 01期
关键词
Vector space; industrial cluster; information; retrieval;
D O I
10.1515/phys-2019-0007
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The current information retrieval research on industrial clusters has low precision, low recall ratio, obvious delay and high energy consumption. Thus, in this paper, a information retrieval algorithm based on vector space for industrial clusters is proposed. By optimizing the unlawful labels in the database network, dividing the web pages of the industrial cluster information database and calculating the keyword scores of the relevant information of the industrial cluster corresponding to a web page, a set of well-divided database pages is obtained, and the purification of the industrial cluster information database is realized. According to the purification of industrial cluster information database, RFD algorithm is used to extract the page data features of purified industrial cluster information database. The extracted results are substituted into the information retrieval, and the vectors composed of retrieval units are used to describe the information of various types of industrial clusters and each retrieval. The matching results of information retrieval are obtained by calculating the correlation between the information of industrial clusters and the query, and the information retrieval of industrial clusters is completed. Experimental results show that the algorithm has high precision and recall ratio, short retrieval time and low energy consumption.
引用
收藏
页码:60 / 68
页数:9
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