Method and device for matching multi-data-source multidimensional data, equipment and storage medium

Abstract

The invention provides a method and a device for matching multi-data-source multidimensional data, equipment and a storage medium. The method comprises the following steps that: matching each piece offirst data information with multiple dimensions in a first data source with at least one piece of second data information with multiple dimensions in a second data source; screening matched data information pairs with more than two dimensions from a matching result; and on the basis of the weight value of a preset dimension, calculating a similarity between first data information and second datainformation in the data information pair. By use of the embodiment of the invention, matching query among multi-data-source multidimensional data can be realized, a query data size during manual matching is greatly reduced, the human cost of matching query is save, and data matching accuracy is improved.

Description

technical field [0001] Embodiments of the present invention relate to data information processing technology, in particular to methods, devices, equipment and storage media for multi-data source multi-dimensional data matching. Background technique [0002] In the current application system, such as the e-government system, different departments often need to perform multi-dimensional and multi-level data matching across departments to query the optimal results. However, project data generation methods and concerns of different departments are different, and data sharing and matching are rarely carried out. [0003] Currently, the following two matching methods are mainly used: [0004] 1) Manual matching: manual matching requires each business person to be proficient in all data rules and the relationship between the dimension values ​​of the policy, especially for data with subordinate-subordinate relationships or data with a large amount of data, which is of great import...

AI Technical Summary

Problems solved by technology

[0004] 1) Manual matching: manual matching requires each business person to be proficient in all data rules and the relationship between the dimension values ​​of the policy, especially for data with subordinate-subordinate relationships or data with a large amount of data, which is of great importance to the business The staff has extremely high requirements, and problems such as inaccurate matching and low matching efficiency are prone to occur;

[0005] 2) Single-dimension matching: convert the data of different departments into data format through data interface, convert the data format into the data structure required by the department, and then perform matching and fusion according to a single dimension, or establish matching of all data from different departments After the relationship, manual project matching is performed. Most of the departmental data is now multi-dimensional data, and matching based on only a single dimension has great limitations.

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