Enterprise activeness analysis method based on big data mining
An analysis method and activity technology, applied in the field of enterprise management, can solve problems such as the inability to intuitively, completely and accurately display the status of enterprise activity, complex calculation process, and poor calculation efficiency, so as to improve calculation targeting and improve calculation efficiency. Efficiency, the effect of simplifying calculations
Active Publication Date: 2020-12-01
四川云恒数联科技有限公司
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Problems solved by technology
Most of the evaluation methods for enterprise activity in the prior art are to establish a set of index system to judge the enterprise activity value, which has great limitations and incompleteness, the calculation process is complicated and the calculation efficiency is poor, and it cannot be reported to the management. Personnel intuitively, completely and accurately display the activity status of enterprises in the managed area
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[0026] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be further elaborated below in conjunction with the accompanying drawings.
[0027] In this example, see figure 1 As shown, the present invention proposes a method for analyzing enterprise activity based on big data mining, comprising steps:
[0028] S10, obtain all enterprise data in the region from the multi-dimensional enterprise official management organization in the evaluation area, and integrate the multi-source enterprise data to obtain the enterprise big data in the evaluation area;
[0029] S20, extracting feature values from the enterprise big data, constructing enterprise big data with feature labels; classifying the enterprise big data into industries according to the feature labels, and arranging according to the industry activity of each industry in all industries included in the enterprise big data , to construct an industry mat...
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The invention discloses an enterprise activeness analysis method based on big data mining. The method comprises the steps of obtaining enterprise big data from a multi-dimensional enterprise officialmanagement institution of an evaluation region; carrying out industry division on the enterprise big data, and constructing an industry matrix H with an activity level; performing subordinate analysison each industry element in the industry matrix, and constructing an enterprise matrix Q with an activity level; and establishing an enterprise activity network diagram, and displaying the obtained enterprise activity network diagram to a manager. According to the method, through multi-dimensional grading processing analysis, on the basis of the calculation efficiency, an enterprise activity guidance result which accurately fits the actual situation can be obtained; management personnel can visually, completely and accurately obtain the activity state of each enterprise in the managed area, so that the management personnel can be helped to effectively control the accurate object, and the enterprise management efficiency is improved.
Description
technical field [0001] The invention belongs to the technical field of enterprise management, and in particular relates to an enterprise activity analysis method based on big data mining. Background technique [0002] With the rapid development of social development and national economy, there are more and more enterprises in each region, which makes the overall management of enterprises more difficult. How to monitor each enterprise to each enterprise from a macro perspective Effective management is also increasingly complex. [0003] Enterprise activity is an important indicator that can measure the status quo of enterprise development. Most of the evaluation methods for enterprise activity in the prior art are to establish a set of index system to judge the enterprise activity value, which has great limitations and incompleteness, the calculation process is complicated and the calculation efficiency is poor, and it cannot be reported to the management. Personnel intuiti...
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IPC IPC(8): G06F16/26G06F16/953G06Q10/06
CPCG06Q10/06393G06F16/26G06F16/953
Inventor 郑伟陈浩朱正华许武
Owner 四川云恒数联科技有限公司