Using Dynamic Semantic Network to Construct Knowledge Base

Knowledge base building is a key branch of modern artificial intelligence research. Current methods in this field mainly focus on computational efficiency, decidability, data exchange, and machine readability. In this paper, a novel human like knowledge representation method called dynamic semantic network (DSN) is proposed. With the inspiration of high level human brain cognitive models, DSN aims at building more practical and abundant knowledge base. The inference and learning mechanism on DSN are latterly studied. And the construction issues are also discussed.