Graph storage optimization method and device and electronic equipment

Abstract

The invention discloses a graph storage optimization method and device, electronic equipment and a computer readable medium. The method comprises the following steps: obtaining user information to construct a knowledge graph which comprises nodes representing entities or concepts and edges representing relationships; setting a folding rule to select nodes in the knowledge graph as folding nodes; identifying a first-degree associated node of the folding node; establishing a one-degree edge expansion relationship between every two one-degree associated nodes of the same folding node; and optimizing the knowledge graph structure based on the first-degree edge expansion relationship and storing the knowledge graph structure. According to the method, the knowledge graph structure can be optimized by establishing the direct connection relation between the first-degree association nodes of the folding nodes, and the calculation amount of knowledge graph query is reduced.

Description

technical field [0001] The present invention relates to the field of computer information processing, in particular to a graph storage optimization method, device, electronic equipment and computer readable medium. Background technique [0002] In the financial anti-fraud scenario based on big data, the real information and in-depth features of users can be obtained through knowledge graphs, and the false information registered by users can be verified. Therefore, in anti-fraud scenarios, knowledge graphs are very effective means. [0003] Folding query is a common operation to obtain user's deep features through knowledge graph. In a super large graph with one billion vertices and tens of billions of edges, the existing query algorithm is used to perform two-degree folding query, that is, the non-folding four-degree query scale, which requires a very large amount of calculation, and the folding query operation occupies too many computing resources. Moreover, the calculati...

AI Technical Summary

Problems solved by technology

In a super large graph with one billion vertices and tens of billions of edges, the existing query algorithm is used to perform two-degree folding query, that is, the non-folding four-degree query scale, which requires a very large amount of calculation, and the folding query operation occupies too many computing resources. Moreover, the existing folding query calculation speed is slow and cannot meet the performance requirements

In the existing technology, technicians often reduce the amount of query calculation by improving the query algorithm, and there are few attempts to reduce the amount of query calculation by optimizing the knowledge map storage structure

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