Research Article
Research on the Construction and Application of Knowledge Graph in the Field of Open Data Policy
@INPROCEEDINGS{10.1007/978-3-031-30237-4_13, author={Gao Lu and Xingli Liu and Jianghong Ou and Dahua Fan}, title={Research on the Construction and Application of Knowledge Graph in the Field of Open Data Policy}, proceedings={Machine Learning and Intelligent Communication. 7th EAI International Conference, MLICOM 2022, Virtual Event, October 23-24, 2022, Proceedings}, proceedings_a={MLICOM}, year={2023}, month={4}, keywords={Policy Text Analysis Named Entity Recognition Bi-LSTM + CRF Knowledge Graph Data Open Policy}, doi={10.1007/978-3-031-30237-4_13} }- Gao Lu
Xingli Liu
Jianghong Ou
Dahua Fan
Year: 2023
Research on the Construction and Application of Knowledge Graph in the Field of Open Data Policy
MLICOM
Springer
DOI: 10.1007/978-3-031-30237-4_13
Abstract
In this paper, data open policy documents, laws and regulations are used as corpus sources, and the Bi-LSTM + CRF deep learning algorithm is selected to complete the training of the named entity recognition model constructed by the knowledge graph, and realize a collaborative relationship, data openness and data security concepts as the ontology. The knowledge map in the field of data openness policy is used to construct the model to complete the automatic identification and analysis of the collaborative situation of data openness policy text. The final simulation verification shows that the Bi-LSTM + CRF named entity recognition algorithm is more accurate than the CRF + + machine learning model training accuracy P value, recall rate R value and the harmonic average F value have been significantly improved, and the “Outline for Promoting Big Data Development”, a typical data development policy text coordination situation analysis, has been objectively completed from the perspective of data openness and data security.
