hello£¬everyone. After some survey, I get some conclusion: 1. Knowledge graph is a concept made by google. 2. Knowledge graph is a kind of knowledge engineering. 3. Knowledge engineering has two components: knowledge base and inference engine. 4. Knowledge engineering has two schools of thought: rationalism and empiricism. 5. Rationalism derive rule-based approach and empiricism derive statistic-based approach. 6.The rule-based approaches value the soundness and completeness of the inference engine and the statistic-based approach value the richness of the knowledge base. 7.The OWL is a kind of rule-based approach and the vector-based approach is a kind of statistic-based approach. 8.In the internet, the knowledge base is huge.It is always impossible to do a complex inference on a huge knowledge base. My question is: In google, is the statistic-based approach the main approach? Is the OWL used in google¡¯s knowledge graph? Besides Google search engine£¬ is there any other successful application of the knowledge graph? Besides knowledge graph, is there any other successful knowledge engineering in the industrial world£¿Received on Sunday, 21 October 2018 03:39:55 UTC
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