Automatic circulation method of user electricity demand work order based on NLP information extraction and few-sample self-learning

The invention discloses an automatic circulation method of a user electricity demand work order based on NLP information extraction and few-sample self-learning. The method comprises the steps of 1, extracting acceptance content and user information of the user electricity demand work order by using RPA, and constructing a work order distribution model; 2, structuralizing irregular acceptance content texts by adopting an NLP information extraction method, and extracting key information of the electricity demand work order of the user; 3, inputting the key information into a work order distribution model, and achieving automatic distribution of part of the user electricity demand work orders; 4, recording and training a work order disposal result of manual order distribution by adopting a few-sample learning method of natural language processing to form a new self-distribution path, and updating the work order distribution model; and 5, inputting the key information obtained in the step2 into the updated work