The text recognition of power grid customer service work orders has profound significance for the market operation of power enterprises,and can provide necessary data support for the intelligent promotion of the power grid.This research proposes an automatic text recognition method for power grid customer service work orders based on natural language processing.The improved HanLP word breaker is used to segment words,and the data representation of the text is obtained through the cross language pre train-ing model,and the text is recognized by combining the attention mechanism and the two-way short-term memory model.The experi-mental data shows that under the first level classification directory of the work order,the accuracy of the proposed model test set can reach 98.3％,with accuracy,recall,and F1 scores of 95.3％,94.7％,and 95.0％,respectively.Under the secondary classification directory,its evaluation index remains above 90％.The model has excellent performance in text recognition of power grid customer service work orders.
关键词
自然语言处理/电网工单/文本识别/跨语言预训练/双向长短时记忆/注意力机制
Key words
natural language processing/power grid work order/text recognition/cross-lingual language model/bidirectional long short-term memory/attention mechanism
维普
万方数据