The process of constructing a knowledge graph is a continuous iterative process that combines human and machine efforts, primarily driven by machine learning, alongside expert definitions and corrections. The work requiring human intervention includes Schema definition, preparation of partially structured knowledge, and verification of machine learning results. Based on user feedback, the increase and update of corpus, the model is continuously updated and iterated.
The knowledge graph in the professional field has been constructed, and after combining its unique application form with domain data and business scenarios, it will practically assist enterprises in achieving actual commercial value in this field. Nowadays, knowledge graphs have been successfully applied in many industries.
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