TY - GEN
T1 - An Aviation Manufacturing Process Knowledge Question-Answering System Based on Knowledge Graph
AU - Qin, Linhao
AU - Zhang, Hongpeng
AU - Ming, Zhenjun
AU - Lv, Ruiqiang
AU - Du, Tingting
AU - Lu, Hu
AU - Li, Qiang
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - This paper introduces a question-answering system based on a knowledge graph of the aviation manufacturing process. By collecting and extracting knowledge in the fields of machining, assembly, forming, materials, and other relevant aspects of aviation manufacturing technology, we first construct a comprehensive knowledge graph within the domain. We then leverage natural language processing technologies to address natural language queries. This encompasses named entity recognition utilizing the Aho-Corasick algorithm and Levenshtein Distance, rule-based intention recognition, query template matching and instantiation, among other techniques. Subsequently, answers are retrieved from the established knowledge graph. The test results demonstrate a precision rate of knowledge retrieval at 94.86%, enabling fast and accurate responses to the majority of questions within this domain.
AB - This paper introduces a question-answering system based on a knowledge graph of the aviation manufacturing process. By collecting and extracting knowledge in the fields of machining, assembly, forming, materials, and other relevant aspects of aviation manufacturing technology, we first construct a comprehensive knowledge graph within the domain. We then leverage natural language processing technologies to address natural language queries. This encompasses named entity recognition utilizing the Aho-Corasick algorithm and Levenshtein Distance, rule-based intention recognition, query template matching and instantiation, among other techniques. Subsequently, answers are retrieved from the established knowledge graph. The test results demonstrate a precision rate of knowledge retrieval at 94.86%, enabling fast and accurate responses to the majority of questions within this domain.
KW - Knowledge graph
KW - Process knowledge question-answering
KW - Smart manufacturing
UR - http://www.scopus.com/inward/record.url?scp=85193265720&partnerID=8YFLogxK
U2 - 10.1007/978-981-97-0194-0_53
DO - 10.1007/978-981-97-0194-0_53
M3 - Conference contribution
AN - SCOPUS:85193265720
SN - 9789819701933
T3 - Lecture Notes in Mechanical Engineering
SP - 539
EP - 547
BT - Proceedings of Industrial Engineering and Management - International Conference on Smart Manufacturing, Industrial and Logistics Engineering and Asian Conference of Management Science and Applications
A2 - Chien, Chen-Fu
A2 - Dou, Runliang
A2 - Luo, Li
PB - Springer Science and Business Media Deutschland GmbH
T2 - 3rd International Conference on Smart Manufacturing, Industrial and Logistics Engineering, SMILE 2023 and the 7th Asian Conference of Management Science and Applications, ACMSA 2023
Y2 - 17 November 2023 through 19 November 2023
ER -