Abstract
In the context of the rapid development of the modern economy, information is particularly important in the economic field, and information determines the decision-making of enterprises. Therefore, how to quickly dig out information that is beneficial to the enterprise has become a crucial issue. This topic applies data mining technology to economic intelligent systems and obtains the data object model of economic intelligent systems through the integration of information. This article analyzes the interrelationship between its objects on this basis and uses data mining-related methods to mine it. The establishment of economic intelligence systems not only involves the establishment of mathematical models of economic systems, but also includes research on the algorithms applied to them. How to apply an algorithm to quickly and accurately extract the required economic intelligence domain information from the potential information in the database, or to provide a method to find the best solution, involves the use of association rules and classification prediction methods. The application of data mining algorithms can be used to study the application of economic intelligence systems. This paper develops and designs an economic intelligence information database and realizes the economic intelligence system on this basis, and realizes the research results. Finally, this paper has tested the dataset, and the results show that the classification accuracy of this algorithm is 2.64% higher than that of the ID3 algorithm.
Highlights
Following the Internet, digital mining has become a new research hotspot, especially in high-dimensional, large-scale, distributed digital mining, which has broader prospects, and the potential economic value is limitless
Li and Long studied image detection and quantitative detection analysis of gastrointestinal diseases based on data mining [1]
Xu et al look at privacy issues related to data mining from a broader perspective and study various methods that help protect sensitive information
Summary
Following the Internet, digital mining has become a new research hotspot, especially in high-dimensional, large-scale, distributed digital mining, which has broader prospects, and the potential economic value is limitless. Zuo researched and analyzed the characteristics of network viruses and designed a computer data mining module He combined the data mining technology with the dynamic behavior interception technology to mine hidden information and determine whether there is a virus. He applied this method to network Trojan virus detection [2]. Xu et al look at privacy issues related to data mining from a broader perspective and study various methods that help protect sensitive information. He reviewed the most advanced methods and put forward some preliminary ideas for future research directions [4]. Hong et al proposed a new method to construct a flood sensitivity map in Poyang County, Jiangxi
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