End-to-end-based large-scale knowledge graph construction and storage method and end-to-end-based large-scale knowledge graph construction and storage system

Abstract

The invention discloses an end-to-end-based large knowledge graph construction and storage method and system. The system comprises a knowledge graph construction system, a knowledge construction module, a knowledge management module, a knowledge application module, a knowledge extraction module, and a processing and storage module. The knowledge graph construction system is in communication connection with the knowledge construction module, the knowledge management module, the knowledge application module, the knowledge extraction module and the processing storage module. The knowledge construction module comprises a knowledge collection module, a knowledge fusion module, a knowledge evaluation module and a knowledge updating module; the knowledge application module comprises a cognition service module, a language understanding module and an inference engine module; the reasoning engine module is in communication connection with the understanding service module and the language understanding module, and the language understanding module is in communication connection with the understanding service module. According to the invention, required data can be obtained more quickly and efficiently; through cooperation of data integration, data cleaning and data updating in the data cleaning and perfecting module and the processing and storing module, quick search is facilitated.

Description

technical field [0001] The present invention relates to the technical field of data processing, in particular to an end-to-end large-scale knowledge map construction and storage method and system. Background technique [0002] In a narrow sense, the knowledge graph is a new concept proposed by Google in 2012, which is used by Internet companies to organize network data from a semantic perspective, thereby providing a large knowledge base for intelligent search services. Formally, a knowledge graph is a knowledge carrier represented by a graph data structure, which describes things in the objective world and their relationships. Nodes represent things in the objective world, and edges represent relationships between things. Knowledge graphs are indispensable for artificial intelligence applications. Basic resources; at present, knowledge graphs have been implemented in many vertical fields such as finance and e-commerce, and high-quality knowledge has gradually become one of ...

AI Technical Summary

Problems solved by technology

At present, there are the following problems in the construction of knowledge graphs: the construction of knowledge graphs has rich data in the database, and the client cannot identify and filter effective data well when searching and obtaining. At the same time, the integration and separation of data in the database is inconvenient, resulting in search Low efficiency, data storage update and data screening are not fast enough

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