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16 August 2023 A comprehensive energy services knowledge graph completion method based on a filter-feedback mechanism
Han Zhang, Jiaju She, Yingqiu Wang, Meng Zhao, Zecheng Wu, Yanpin Wu
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Proceedings Volume 12787, Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023); 1278705 (2023) https://doi.org/10.1117/12.3004685
Event: 6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023), 2023, Shenyang, China
Abstract
In order to achieve a balanced breadth and depth of knowledge graph in the energy domain and alleviate the high complexity of information sources during energy service, a comprehensive energy service knowledge graph construction and completion method based on a filter-feedback mechanism is proposed. Firstly, the domain filtering mechanism is designed to filter the information in the input text unrelated to the energy domain by calculating the entity commonality. Then, a feedback mechanism is constructed using third-party information to complete the missing entities or relations in the triplet. The method is validated on energy domain and public datasets, and experimental results demonstrate that the accuracy of domain knowledge discrimination exceeds 90%. Moreover, its performance is comparable to that of the public dataset.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Han Zhang, Jiaju She, Yingqiu Wang, Meng Zhao, Zecheng Wu, and Yanpin Wu "A comprehensive energy services knowledge graph completion method based on a filter-feedback mechanism", Proc. SPIE 12787, Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023), 1278705 (16 August 2023); https://doi.org/10.1117/12.3004685
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KEYWORDS
Data modeling
Transformers
Design for manufacturing
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