Information retrieval algorithm of industrial cluster based on vector space

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Abstract

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 purication of the industrial cluster information database is realized. According to the purication of industrial cluster information database, RFD algorithm is used to extract the page data features of puried 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.

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APA

Li, R., & Hassan, N. (2019). Information retrieval algorithm of industrial cluster based on vector space. Open Physics, 17(1), 60–68. https://doi.org/10.1515/phys-2019-0007

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