A Method to Evaluate the Credibility of Domain Knowledge Network Using Validated Expert Knowledge

We are living in an era of knowledge explosion, where all kinds of knowledge are emerging and becoming more and more complicated with the development of new techniques and new ideas. When we study knowledge and apply them to understand and solve problems, the credibility of knowledge is becoming our main concerns. Usually, high credible domain knowledge can guide us correctly understand all concepts and the relationships between them in this domain. Due to its good layer structure and scalability, domain knowledge network is widely used to represent knowledge in knowledge engineering, artificial intelligence and others in recent years. How to ensure the credibility of domain knowledge network? This is an important and interesting topic. In this paper, we propose a method to evaluate the knowledge credibility for domain knowledge network, which means that we can start from the layer structure of domain knowledge network, and evaluate the credibility of knowledge layer by layer using validated expert knowledge such as domain dictionary, domain ontology and domain expert experience. We conduct experiments with six domain knowledge network constructed based on network data and six domain knowledge network constructed manually based on published books or domain dictionaries, which describe the same domain knowledge in pairs. Experimental results show that the knowledge credibility of domain knowledge network constructed from validated expert knowledge is significantly higher than the knowledge credibility of domain knowledge network constructed directly from network data, which satisfy our expectation and also prove the effectiveness of our credibility evaluation method.