Abstract
AbstractThe 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.
Highlights
The current information retrieval research on industrial clusters has low precision, low recall ratio, obvious delay and high energy consumption
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
Experiment 3: (a) Query delay of tree matching algorithm based on (b) Query delay of keyword retrieval based on tempoe ective path weight ral semantics (c) Information query delay based on Top-k (d) Similarity query delay for high dimensional data based on Chi square distribution (e) Query delay of industrial clusters information retrieval based on vector space ment coe cient of information and retrieval is the largest, which means that the vector can describe information and query content to the greatest extent
Summary
Abstract: The current information retrieval research on industrial clusters has low precision, low recall ratio, obvious delay and high energy consumption. According to the puri cation of industrial cluster information database, RFD algorithm is used to extract the page data features of puri ed 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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