Knowledge graph construction method and device, electronic equipment and storage medium

Abstract

The invention relates to a big data technology, and discloses a knowledge graph construction method. The method comprises the following steps of: extracting entity information and correlations in an original data set, and creating node attributes and node relations according to the entity information and the correlations; analyzing a service data table corresponding to the original data set to obtain a header information set; enabling the header information set to respectively correspond to the node attributes and the node relations through entity links to obtain node attribute values and noderelation values, and summarizing the node attribute values and the node relation values to obtain an analysis value set; and obtaining a standard graph query statement according to the analysis valueset and a pre-constructed graph query statement template, and obtaining a knowledge graph according to the standard graph query statement. In addition, the invention also relates to a blockchain technology, and the original data set can be from nodes of a blockchain. The invention further provides a knowledge graph construction device, electronic equipment and a storage medium. According to the knowledge graph construction method and device, the electronic equipment and the storage medium of the invention, the threshold of knowledge graph construction can be reduced.

Description

technical field [0001] The present invention relates to the field of big data technology, in particular to a knowledge map construction method, device, electronic equipment and computer-readable storage medium. Background technique [0002] Under the background of big data, the scale of data is expanding rapidly, the data forms are diverse, and the requirements for data applications are also increasing. With the expansion of business, the amount of data has increased sharply, leading to the gradual emergence of the storage capacity problem of a single data node. Simply expanding the hard disk to improve storage capacity will increase the risk of failure, resulting in data loss, server downtime and other phenomena. [0003] As a new data form, knowledge graph can solve the problem of data node storage capacity by extracting and unifying associated data entities. Under the existing technology, using a graph database to construct and store knowledge graphs has the following de...

AI Technical Summary

Problems solved by technology

Under the existing technology, using a graph database to construct and store knowledge graphs has the following defects: 1. For the user interface, the graph database itself only provides an interactive interface based on the Cypher language, and different Cypher statements are required for different data. When it is too large, a large number of Cypher statements are required, which will take up a lot of computer resources and be unfriendly to operate

2. Professional R&D personnel are required to write the Cypher language to create and query graphs, so it is very difficult for non-R&D personnel to define a knowledge graph in the graph database, and it is basically impossible to operate

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