Question and answer systems have a long history of development, and with the maturity of knowledge graph technology in recent years, knowledge graph-based question and answer systems are gradually applied to many fields. In this paper, we first discuss the concept of knowledge graph and question and answer system, and then analyze the key technologies used in it. Before dealing with linguistic problems, questions need to be structured and represented by semantic parsing and space vector-based modeling are common approaches. The question and answer system can be divided into three parts: question classification, entity recognition, and relationship extraction, for each of which a large number of techniques have been studied. Finally, a question and answer system based on the knowledge graph of chronic diseases is designed to provide a proven solution for this field, in view of the problem that there are many patients with chronic diseases but lack of sufficient knowledge of the diseases.

Zhaoyang Cao, Lin Ni, Lirong Dai. A Review of Knowledge Graph-based Question and Answer System Research and Its Application in Chronic Disease Diagnosis. Academic Journal of Computing & Information Science (2021), Vol. 4, Issue 4: 1-11. https://doi.org/10.25236/AJCIS.2021.040401.

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