Intelligent Mining Method of Distribution Line Trip Filling Text

As a frequent fault of distribution network, the accumulated large number of trip documents are mainly handled manually, which is inefficient and has strong subjective factors. In order to solve this problem, in order to constitute a complete text causality fault phenomenon and the cause of the problem for mining the goal, put forward an intelligent power distribution line tripping fill in text mining method, the method using the distribution trip provided text narrative logic characteristics, puts forward the fusion of word segmentation and part of speech and syntactic analysis results trip provided text extraction strategy; On this basis, a two-stage filtering method is proposed. Firstly, the distributed high-dimensional vector similarity is used to realize the preliminary filtering, and then the final result of text mining is determined based on the text editing similarity. A case study based on a province shows that the accuracy of the proposed method can reach more than 72%, which significantly improves the efficiency of text processing and can initially meet the actual needs.