Intelligent classification method for complaint work orders from customer service center

Abstract

The invention relates to a data processing method, in particular to an intelligent classification method for complaint work orders from a customer service center. The method is implemented as follows:a synonym database and a stop word database are established; synonym definition is carried out based on information of accepted contents of work orders so as to solve problems of inconsistent description words for a same problems by clients in different areas in voice telephone traffic and the like; text segmentation is carried out; to be specific, text segmentation is carried out based on the established synonym database and stop word database and part-of-speech tagging is carried out on the segmentation vocabulary; word frequency statistics is carried out; to be specific, a client complaintperception information word cloud chart is formed and word frequency statistics is carried out to reflect the client complaint perception visually; and document work order theme extraction is carriedout. Therefore, a problem that the user perception can not be obtained effectively and accurately from electricity user complaint work orders and return-visit dissatisfaction work orders can be solved.

Description

Technical field: [0001] The invention relates to a data processing method, in particular to a method for intelligently classifying complaint work orders in a customer service center. Background technique: [0002] At present, in the process of 95598 customer service, the user is mainly perceived through the expert experience method. In the big data environment, the expert experience method will not be able to meet the actual application needs; the existing users' perception of the radio station area and customer complaint hotspots is mainly through statistical analysis. Method perception; the current user perception, intelligent identification of large categories of characteristics, can not effectively perceive the specific reasons of users, such as the work attitude of front-line staff, work norms, etc.; cannot perceive customer needs through customer service complaint work orders and dissatisfaction work orders , The specific reasons for complaints or customer return visit...

AI Technical Summary

Problems solved by technology

[0002] At present, in the process of 95598 customer service, the user is mainly perceived through the expert experience method. In the big data environment, the expert experience method will not be able to meet the actual application needs; the existing users' perception of the radio station area and customer complaint hotspots is mainly through statistical analysis. Method perception; the current user perception, intelligent identification of large categories of characteristics, can not effectively perceive the specific reasons of users, such as the work attitude of front-line staff, work norms, etc.; cannot perceive customer needs through customer service complaint work orders and dissatisfaction work orders , the specific reasons for complaints or customer return visits to deal with unsatisfactory work orders, the hot spots of customers' appeals in sensitive areas and characteristic areas, cannot be grasped in time, which will affect the improvement of customer service quality

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