摘要：【中文】本发明提供了一种基于知识图谱分析的装备试验体系规划决策的方法和系统，以任务模板的方式对试验信息进行采集并结构化入库，得到原始试验数据，对原始试验数据进信息预处理，得到知识数据；利用自然语言处理对知识数据进行信息抽取、知识融合，构建试验知识图谱，并呈现可视化的试验知识图谱；采用机器学习，对试验知识图谱进行文本挖掘后，输出试验体系规划决策。本发明通过将试验信息进一步组织和抽象成试验知识，进行知识实体节点之间关联以及与元数据的关联挖掘，最终以知识节点的多属性关联为基础，构建了多源异构试验知识图谱并进行图谱的可视化呈现，为试验体系规划决策提供有力支撑。 【EN】The invention provides a method and a system for planning and deciding an equipment test system based on knowledge graph analysis, wherein test information is acquired in a task template mode and structurally warehoused to obtain original test data, and the original test data is subjected to information preprocessing to obtain knowledge data; extracting information and fusing knowledge from knowledge data by natural language processing, constructing a test knowledge graph, and presenting a visual test knowledge graph; and (4) adopting machine learning to perform text mining on the test knowledge graph, and outputting a test system planning decision. According to the invention, test information is further organized and abstracted into test knowledge, association between knowledge entity nodes and association mining with metadata are carried out, and finally, a multi-source heterogeneous test knowledge graph is constructed and visualized presentation of the graph is carried out on the basis of multi-attribute association of the knowledge nodes, so that powerful support is provided for planning decision of a test system.