Multi-structuralized data accessing method based on semantic dependence

Abstract

The invention discloses a multi-structuralized data accessing method based on semantic dependence. The method comprises the following steps of (10), user log-in, wherein a user body is labeled, and auser semantic dependence set of the user body based on the semantic dependence is obtained; (20), user global view obtaining, wherein according to the labeled user body and the user semantic dependence set, a global view reverse arrangement generating algorithm is adopted to obtain a user global view; (30), global view updating, wherein according to a changing mark, the dynamic change of data source privacy requirements is judged, and the user global view is subjected to semantic correlation updating to obtain a recombined user global view. The multi-structuralized data accessing method is high in information safety and data utilizing efficiency.

Description

technical field [0001] The invention belongs to the technical field of multi-source data access, in particular to a semantic dependency-based multi-structured data access method with good information security and high data utilization efficiency. Background technique [0002] Usually through effective access control, an effective user-oriented access view is obtained to ensure information security. [0003] The traditional database has a single structure and is based on entity objects. The relationship between entities is clear and there are common patterns to follow. Therefore, there are patterns before data. Data management and access control can be integrated in a top-down manner . However, the current big data has a wide range of sources, various data representation forms, complex structures, and semantics as the standard. The relationship between entities is unstructured. Usually, there is data first and then there is a model. It needs to be fused with big data in a bo...

AI Technical Summary

Problems solved by technology

[0005] The above data access methods rely too much on the redundant structural model of the data composition itself, while ignoring the essence of the direct semantic association of the data, which will not only result in low efficiency of conditional judgment execution, but also cause excessive protection of data value, making it difficult to protect data privacy. A good balance of effectiveness between security and value

[0006] Therefore, the problem existing in the prior art is: under the premise of ensuring information security, the multi-structured data access method has low data utilization efficiency

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