Visual ontology construction system and method for knowledge graph

Abstract

The invention relates to the field of information processing, in particular to a visual ontology construction system and method for a knowledge graph, and the method comprises the steps: drawing an ontology model graph in a mode of adding nodes and edge graphs through the system; and the system generates ontology model data according to a preset data conversion format and stores the ontology modeldata. According to the method, the ontology model is created by adopting a visual drawing mode, so that the logic structure of the ontology model is expressed more intuitively. A user adds entities,event nodes and relation connecting lines in a graph form to create an ontology model graph, complex language description or configuration form filling is not needed, the ontology model drawing process is simple and convenient, and the logic structure of the ontology model is clear in the creating process. The threshold for creating the ontology model is lowered. And a powerful tool and method areprovided for application and popularization of the knowledge graph.

Description

technical field [0001] The invention relates to the field of information processing, in particular to a method and system for creating a visual ontology for knowledge graphs. Background technique [0002] The concept of ontology first originated in the field of philosophy, which refers to the explanation and description of the objective existence system. In essence, it is a formal expression of a certain set of concepts in a specific field and the relationship between them. The purpose of ontology construction is to classify knowledge terms in a field, and at the same time specify the relationship between each classification and their own attributes. [0003] Ontology models can be constructed manually with the help of ontology editing software, or in a data-driven, automated manner. The automatic construction includes three stages: entity parallel relationship similarity calculation, entity hyponymy relationship extraction, and ontology generation. In the actual engineer...

AI Technical Summary

Problems solved by technology

This method is difficult to verify whether the ontology meets the business requirements at the earliest possible stage, and errors in entities and relationships are often discovered after the graph is generated

After an error is found, it is necessary to re-modify the table configuration, perform data mapping, and generate a map. The cost of iterative error correction is very high

[0005] Specifically, traditional ontology editing and management tools such as: Protégé tools need to define ontology classes, relationships and rules between classes when building ontology models, the setting and definition process is complex and cumbersome, and in the process of configuring ontology, The ontology model structure is implicit and invisible; the model structure can only be viewed after the model configuration is completed

If there is an error in the definition and configuration of a certain link in the definition process, it cannot be displayed immediately; the process is more complicated, and only personnel with high professional accomplishment can build the ontology model

However, other ontology construction tools are more complicated to use, and generally need to write a complex ontology representation language; the creation process is invisible, it is not easy to perform logic verification, the creation efficiency is low, and the interaction is poor

Not only that, the general domain ontology model is created, the business logic is limited to the corresponding domain, the reusability is poor, and it is difficult to promote

The existence of these factors makes the professional threshold for ontology creation and knowledge map application relatively high, which limits the scope of knowledge map use

[0006] With the rise of the big data era, knowledge graphs are being used in more and more fields as the most important survey tool, and the demand for ontology models as the framework and logical lines of knowledge graphs is increasing; the traditional complex ontology model creation and Editing tools and methods can no longer meet the needs of technology development and promotion

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