Military equipment knowledge graph-oriented key information query method

A knowledge map and key information technology, which is applied in the field of key information query for military equipment knowledge maps, can solve the problems of lack of a large number of open knowledge sources, difficult large-scale training of deep learning methods, and limited forms of problems in the field of military equipment.

Pending Publication Date: 2022-04-15
中国人民解放军军事科学院战争研究院
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Problems solved by technology

[0004] Compared with open domain question answering, the question form in the field of military equipment is limited, lacks a large num

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  • Military equipment knowledge graph-oriented key information query method
  • Military equipment knowledge graph-oriented key information query method
  • Military equipment knowledge graph-oriented key information query method

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Embodiment Construction

[0035] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, and the present invention will be further elaborated.

[0036] First, combine the figure 1 The key information query method for military equipment knowledge graph according to the embodiment of the present invention is described, which is used to answer four typical query sentences of military equipment, and its application scenarios are very wide.

[0037] Such as figure 1 As shown, the key information query method for military equipment knowledge graph in the embodiment of the present invention has the following steps:

[0038] In S1, as in figure 1 As shown in Fig. 1, the natural language query statement is obtained, and based on the longest common substring match, the entities involved in the natural language query statement are linked to the existing entities in the military equipment knowledge map, and multiple entity link results a...

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Abstract

The invention discloses a military equipment knowledge graph-oriented key information query method, which comprises the following steps of: acquiring a natural language query statement, and performing entity linking on entities involved in the natural language query statement and existing entities in a military equipment knowledge graph based on longest common substring matching to obtain a key information query statement; obtaining a plurality of entity linking results; sorting the plurality of entity linking results based on longest prefix matching, and selecting an optimal entity linking result; creating a query template library according to element types in the natural language query statements; on the basis of template matching, the elements in the natural language query statement are matched with the query template library, the corresponding elements in the natural language query statement are filled into the corresponding atlas query statement templates in the query template library, a complete atlas query statement is formed, and a query result is obtained after atlas query. And four typical query statements of military equipment can be answered without data set and algorithm training.

Description

technical field [0001] The invention relates to the technical field of key information query of knowledge graphs, in particular to a key information query method for knowledge graphs of military equipment. Background technique [0002] The core of the knowledge graph question answering task (knowledge graph question answering KGQA) is to map natural language questions into graph database query statements. The methods to solve this problem are divided into two categories: methods based on semantic analysis and methods based on information retrieval. [0003] In the open question answering of the general knowledge graph, the semantic analysis method and the information retrieval method using the deep neural network can play a very good role. [0004] Compared with open domain question answering, the question form in the field of military equipment is limited, lacks a large number of open knowledge sources, requires high accuracy of answers, and is difficult to use deep learnin...

Claims

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Application Information

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IPC IPC(8): G06F16/332G06F16/36G06F40/253
CPCG06F16/3329G06F16/367G06F40/253
Inventor 尹峻松林波朱思宇罗常伟孔德照黄今辉
Owner 中国人民解放军军事科学院战争研究院
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