Base on the algorithm of natural language processing

semantic similarity and entity identification

an intelligent semantic automatic inspecting system for network complaint work-order is constructed in this paper. It can mine named entities

incidents and relationships of natural language in receipts. Trough feature extraction

model construction

semantic generalization and matching degree calculation

the semantic key information needed for quality inspection is output

and intelligence improvement of traditional quality inspection method for network complaint work order is realized. Meanwhile

this paper designs and implements a method to construct the generalization of expert rules for complaint work orders

it can complement the feature words grown out of limited expert rules and improve the generalization performance of semantic quality inspection. Compared with the traditional keyword matching algorithm

this method has better recognition accuracy

it can effectively reduce the re-dispatch rate of complaints from operators and improve customer satisfaction.