The process of constructing a knowledge graph is a continuous iterative process that combines human and machine efforts, primarily driven by machine learning, along with expert definitions and corrections. The work requiring human intervention includes schema definition, preparation of partially structured knowledge, and validation of machine learning results. Based on user feedback and the increase and updating of corpora, the model is continuously updated and iterated.
The knowledge graph in the specialized field has been successfully constructed. When combined with its unique application forms, field data, and business scenarios, it will effectively assist enterprises in achieving tangible commercial value in that field. Nowadays, knowledge graphs have been successfully applied in many industries.
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