Abstract

The professional vocabulary of the electric power industry is numerous, and the relationship is complex. How to mine valuable information from multi-source data of the power industry and describe the relationship between words is of great significance to assisting multi-business management of power systems. Aiming at the multimodal knowledge data of power systems, this paper uses the BiLSTM-CRF model and BiLSTM-Attention model to extract entity knowledge and relationship, respectively, and identifies image data through the CNN model. The experimental results show that the power industry knowledge graph based on multi-modal deep learning constructed in this paper can better realize the intelligent representation and management of many kinds of business in the power industry.

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