EPC management GNN knowledge fusion method based on knowledge graph

Abstract

Water conservancy EPC enterprises have accumulated rich management and experience knowledge in the whole life cycle of the project. In order to solve the problem that enterprise management knowledge has trouble updating and growing, a knowledge fusion method of water conservancy EPC enterprise management based on GNN is proposed. Firstly, the knowledge architecture of water conservancy project management and EPC enterprise management is analyzed, and the data layer of knowledge graph is constructed according to relevant standard specifications and process documents to form the thematic knowledge graph of each module. Then, the knowledge graph of each topic ontology is mapped by instance named entity recognition technology. Then, the graph neural network is used to align the entities to ensure the integration of thematic knowledge. Finally, the Yangtze River protection project is taken as an example to verify the case, and the integration of thematic knowledge map is completed in combination with each stage of EPC project management. The result show that the named entity recognition uses a model based on RoBERTa-wwm-ext, and achieves an F1 value of 0.895, showing good result. In terms of entity alignment, using the AttrGNN method, its Hits@1 and MRR values reached 97.6 and 0.97, respectively, showing a significant improvement. This study provides new ideas and method for improving the management efficiency of water conservancy EPC enterprises and promoting the improvement of management level, which has important theoretical and practical significance.

Keywords

Yangtze River protection EPC / knowledge graph / knowledge fusion / entity alignment / graph neural network