摘要：

Abstract:

【Purpose/significance】 Based on scenario theory and domain knowledge graph, the concept and connotation of scenario

based knowledge graph are proposed to describe the generation and application scenario information of knowledge, thereby improving

the precision and applicability of knowledge graph application.【Method/process】 Firstly, based on scenario theory, knowledge scener⁃

ization, and knowledge graph construction techniques, the definition and structure of scenario-based knowledge graph are proposed;

Secondly, taking the medical scenario-based knowledge graph as an example, a method for constructing the scenario-based knowl⁃

edge graph is proposed. Specifically, a knowledge extraction and fusion method is constructed by combining the BiLSTM-CRF model,

the UIE model, and the rule-based method. The storage and query of scenario-based knowledge graph is implemented using the Neo4j

graph database and the Cypher query language.【Result/conclusion】 Firstly, it is proposed that the scenario-based knowledge graph is

a knowledge graph that describes the attributes of knowledge scenes, and summarizes the characteristics of scene fusion, inheritance,

and reasonability; Secondly, taking mild cognitive impairment as an example to conduct empirical research, the results show that the

current performance of different types of scene extraction is uneven; The overall distribution of various types of scene attributes and

their distribution in different entities are different; In the constructed scenario-based knowledge graph, the fusibility, inheritability,

and reasonability of scene attributes are obvious; Searching based on scene matching can reduce redundancy and error information,

and improve the precision and applicability of results.【Innovation/limitation】 This study further enriches the research on domain

knowledge graph, improving the precision and applicability of knowledge graph applications by describing the generation and applica⁃

tion scenarios of knowledge.