Method and device for generating atlas network

Abstract

The invention discloses a method for generating a graph network, which comprises the following steps of: defining a structure of the graph network, the structure comprising a title node, an element node and a node path; wherein the node path is a relation element between the title node and the element node; obtaining an information source text, analyzing the information source text, and obtaining a text title and text content; and performing structured processing on the text content to generate a graph network. According to the technical scheme, the flexibility of generating the atlas network can be improved, the expansibility is increased, and when various information is associated, the content is clearer and more accurate, and the implementation process is more flexible and more efficient.

Description

Technical field [0001] The invention involves the field of computer applications. Specifically, it involves the generation method and device of a map network. Background technique [0002] Nowadays, the Internet information explosive growth is growing and the source of information is large. In a certain period of time, the amount of information from different sources will increase significantly. In the management of information, each new piece of information is required to control the correlation of information. In the art, the map network is a method that associates various information. [0003] At present, there are many ways to generate graphs network. When the commonly used text association method generates the map network, the connection between the calculation information is easy Applying scenarios requires an additional large number of treatment to improve the accuracy of the correlation; on the other hand, if the structure of the map network is too complicated, multi -lay...

AI Technical Summary

Problems solved by technology

[0003] At present, there are many ways to generate graph networks that are commonly used. When generating graph networks with the commonly used text association method, the relationship between calculated information is likely to be unclear, and it is easy to be interfered by similar words, resulting in association errors, especially in those that require strict associations. In the application scenario, a large amount of additional processing is required to improve the accuracy of the association; on the other hand, if the structure of the graph network is too complex, there will be multiple layers of relationships between element nodes. When forming a graph network, or in the existing When adding new information on the basis of existing information, it needs to be calculated and associated with all existing information, and the amount of calculation is large

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