Portrait construction method based on multivariate heterogeneous data

Abstract

The invention discloses a portrait construction method based on multivariate heterogeneous data, and the method specifically comprises the following steps: S1, respectively importing government affairdata and social data into a government affair resource directory and a social resource directory, carrying out the quality verification of data pairs in the government affair resource directory and the social resource directory, and marking the credible weight of the data; S2, configuring a query use relationship of metadata for the metadata which is qualified in quality check; S3, analyzing a query use relationship of the metadata to generate an sql statement; and S4, taking out the metadata with high credible weight, and based on the taken-out metadata and the metadata query use relationship, constructing a portrait. Fusion cleaning is carried out through multi-source heterogeneous data, and government affair resource directory information resource items with high credible weights are screened out; metadata are established according to business requirements and metadata specifications, models supporting the same logic are called, and if the metadata need to be adjusted, the metadataonly need to be adjusted once, and each model does not need to be reconstructed or adjusted.

Description

technical field [0001] The invention belongs to the field of big data technology, and more specifically, the invention relates to a method for constructing portraits based on multiple heterogeneous data. Background technique [0002] Since government affairs data are also scattered in different database systems of relevant departments, government affairs data as a whole presents the characteristics of massive, disordered, multi-source and heterogeneous. [0003] In the era of big data, government data is no longer limited to simple single-department queries. When it involves multi-department fusion data, the current common problems and processing technologies are: the operation and maintenance team uses SQL to fetch data according to business needs, and executes data through a large number of codes. In the process of business transfer system implementation, there are a lot of repetitive work, cumbersome and opaque processes and other problems. Contents of the invention ...

AI Technical Summary

Problems solved by technology

[0003] In the era of big data, government data is no longer limited to simple single-department queries. When it involves multi-department fusion data, the current common problems and processing technologies are: the operation and maintenance team uses SQL to fetch data according to business needs, and executes through a large number of codes. In the process of business transfer system implementation, there are a lot of repetitive work, cumbersome and opaque processes, etc.

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