Big data based work order type identification method and system and computing device

Abstract

The invention relates to a big data based work order type identification method and system and a computing device. The method comprises the following steps: obtaining a work order to be classified, and performing correlation analysis on a structured field in the work order to be classified to obtain a first correlation coefficient; removing the corresponding structured field in the work order to be classified if the first correlation coefficient exceeds a preset threshold, and obtaining a target work order to be classified; extracting a first feature word of the target work order to be classified, using a pre-constructed naive Bayesian model to calculate the corresponding probability when the type of the work order to be classified is different work order types under the condition that thefirst feature word appears according to the first feature word; and determining the type of the work order to be classified according to the probability corresponding to different work order types. The method can avoid occupying the storage space of a server and lowering the operation efficiency of a service system due to the accumulation of a large number of work orders.

Description

technical field [0001] The present invention relates to the technical field of data processing, in particular to a method, system and computing device for identifying work order types based on big data. Background technique [0002] With the continuous improvement of the digitization of telecommunication networks, large-scale work orders have been formed in telecommunication services. There are more and more types of business work order designs, and it is becoming more and more difficult to identify work order types. At this stage, manual identification of work order types The speed cannot keep up with the rapid growth of business, and the accumulation of work orders takes up a lot of storage space on the server, which directly leads to a decrease in the operating efficiency of the business system. [0003] Therefore, relying on the traditional method of manually identifying work order types cannot meet the needs of telecom business growth in the new era, and new means need ...

AI Technical Summary

Problems solved by technology

[0004] Based on this, it is necessary to provide a big data-based work order type identification method, system, and computing device for the problem that the accumulation of work orders takes up a large amount of storage space on the server and directly leads to a reduction in the operating efficiency of the business system.

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