If we don’t click on the blue words, where do our stories come from?
The process of constructing a knowledge graph is a continuous iterative process that combines human and machine efforts, primarily driven by machine learning, with expert definitions and corrections. The work that requires human intervention includes schema definition, preparation of partially structured knowledge, and verification of machine learning results. Based on user feedback, the increase and updates of corpus, the model is continuously updated and iterated.
The knowledge graph in the professional field has been successfully constructed. When combined with the unique application forms it possesses, domain data, and business scenarios, it will practically assist enterprises in achieving real commercial value in that field. Nowadays, knowledge graphs have been successfully applied in many industries.
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Information source: Higher Education Strategy EDU
This issue editor: Academic Affairs Office, Li Yun