Author(s)

Hongtao Lin

Corresponding Author

Hongtao Lin

Abstract

With the development of artificial intelligence technology, open-domain dialogue systems are attracting more and more attention as a means of intelligent interaction. An open-domain dialogue system aims to create a natural, fluid, and enjoyable dialogue with the user. As a structured representation, a knowledge graph can provide rich semantic information and background knowledge for dialog systems. This paper mainly studies the performance evaluation and optimization strategy of open-domain dialogue systems based on a knowledge graph. First, the knowledge graph network model and the dialogue system protocol specification are introduced. Second, an open-domain dialogue system based on the knowledge graph is designed, which includes a knowledge graph collection module, a conversation preprocessing module, and a conversation recognition module. We introduced the optimization process of the structure, training, and dialogue model parameters. Third, the effectiveness of open-domain dialogue systems based on a knowledge graph is verified by experiments, and various evaluation indicators and methods are used to analyze the results. Finally, this paper's main contributions and innovations are summarized, and future research directions are pointed out. This paper concludes that open-domain dialogue systems based on knowledge graphs improve semantic understanding and logical consistency of dialogue, increase dialogue diversity and fun, achieve high-quality dialogue partners, promote the application of artificial intelligence technology in many fields, and meet the conversational needs of users.

Keywords

Open-domain dialogue systems; Knowledge graph; Performance evaluation; Optimization strategy