Repeated incoming call preprocessing method, device and equipment based on 95598 and storage medium

Abstract

The invention discloses a repeated incoming call preprocessing method, device and equipment based on 95598 and a storage medium. The processing method comprises the following steps: S101, data acquisition; s102, removing business data from the obtained data to obtain screened data; s103, labeling and primary screening are carried out; s104, analyzing the primarily screened data by using text similarity, judging whether the primarily screened data are the same appeal event or not, and if so, inputting the text content of the repeated incoming call corresponding to the primarily selected data into an algorithm unit; if not, sending the primarily selected data to a processing end; s105, the algorithm unit judges whether the received text content is similar or not, if yes, it is considered that the corresponding appeal event is a repeated call, and the repeated call is output; and if not, sending the corresponding text content to the processing end in the step S104. According to the method, the neural network data annotation amount is reduced, the training period is shortened, the text analysis accuracy can be improved, manpower is reduced, and the early-stage preparation time is shortened.

Description

technical field [0001] The invention belongs to the technical field of communication data processing, and relates to a repeated call preprocessing method, device, equipment and storage medium based on 95598 work orders and translated texts. Background technique [0002] Repeated call identification is to find out the repeated calls of the same event and appeal by analyzing the call data of customer appeals, so that business analysts can analyze the repeated calls of customers and the cause of the event. Based on the 95598 work order and translated text, combined with business regulations, the qualified repeated call work orders are screened, and then compared by text similarity algorithm, so as to obtain the repeated call identification result. [0003] For the analysis of text content, the most basic idea is statistics. By counting the frequency of words and words in a large number of articles, we can obtain some information about the rules of words and words, and then use ...

AI Technical Summary

Problems solved by technology

[0006] The text similarity method does not need to obtain a large amount of text in advance and perform text annotation. The preliminary work is relatively simple, but the text similarity has limited ability to distinguish text content, and the effect is not ideal, and it is basically ineffective for some subtle text differences. ;

[0007] The neural network method has a much higher degree of text discrimination, but the neural network needs to collect a large amount of data in the early stage, and manually label it, and then train the labeled data, which requires a lot of manpower and material resources, and needs to be collected in the early stage. A large amount of data, the overhead is much larger than the text similarity method

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