Knowledge graph construction method, device and system and readable storage medium

Abstract

The invention discloses a knowledge graph construction method, device and system and a computer readable storage medium. The method comprises the following steps: acquiring an ontology, an ontology association relationship and an instance identifier corresponding to an instance belonging to the ontology in a network according to equipment information; determining an instance and a corresponding table structure according to the production database, and obtaining a table identifier corresponding to the instance based on the instance and the corresponding table structure; the table structure comprises instance attributes and attribute values; establishing a knowledge graph according to the ontology, the ontology association relationship, the instance identifier corresponding to the ontology and the table identifier corresponding to the instance, wherein the knowledge graph comprises the affiliation relationship between the table identifier and the ontology; the graph in the established knowledge graph can be synchronized with the production database, the structure of the production database does not need to be changed, and the query efficiency is high.

Description

technical field [0001] The embodiment of the invention relates to the technical field of knowledge map, in particular to a knowledge map construction method, device, system and computer-readable storage medium. Background technology [0002] Data is the driving force to promote production. At present, the factory has a large amount of industrial production data, and a large amount of data will be generated every day. They are stored in various databases of the factory. With the development of big data technology, industrial production data has been used in scenarios such as equipment life prediction, optimized production, alarm and so on. As a technology that can show the relationship of knowledge structure and has logical reasoning and calculation, knowledge map can connect the knowledge concept, business scenario and entity structure in a specific field, so as to make the fragmented industrial production data produce more value. [0003] At present, the data acquisition of know...

AI Technical Summary

Problems solved by technology

Among them, when all the data is stored in the graph database, the formed graph is not easy to synchronize with the production database; when all the data is stored in the relational database, it is necessary to redesign the database or change part of the database structure for the existing database site, but the general production database The number of tables and the storage capacity of a single table are relatively large, so it is difficult to change the existing data structure in order to build a knowledge map; if the data is scattered in the graph database and other non-graph databases, the mapping between the ontology and the relational database in the graph database is usually established files, when you need to find data, you need to read the hard disk multiple times, and the query efficiency is low

Images