- From: ÎÒ <1047571207@qq.com>
- Date: Sun, 21 Oct 2018 11:39:03 +0800
- To: semantic-web@w3.org
- Message-Id: <7335B3FB-56BD-44AB-A181-435C460CA0C0@qq.com>
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