A method and system for intelligent dynamic loading of customer service work order information based on machine learning

Abstract

The invention discloses a method and system for intelligent dynamic loading of customer service work order information based on machine learning. It needs to pre-train a scene classification algorithm module and a component display prediction algorithm module, and predict the business scene of customer consultation through the scene classification algorithm module. Confidence is sorted from high to low; after the customer's real scene is determined, all the businesses involved in the customer are constructed, and the abnormal business is predicted through the abnormal detection algorithm, and the components predicted by the component display prediction algorithm module are entered. The component dynamic display interface related to the business scenario and the customer, the component dynamic display interface displays the information components related to the customer and the business, conducts business outlier analysis on the numerical information in the predicted information component, and uses the Gaussian distribution outlier detection algorithm Find possible outliers in the data, and mark the outliers to remind customer service personnel that there may be anomalies in this data.

Description

technical field [0001] The invention relates to the technical field of intelligent dynamic loading of information, in particular to a method and system for intelligent dynamic loading of customer service work order information based on machine learning. Background technique [0002] With the development of artificial intelligence technologies such as machine learning, building a learnable information system has gradually become a trend. Compared with traditional information systems, systems based on artificial intelligence technology make decisions through machine learning algorithms, process business more flexibly, and can greatly improve work efficiency. In the field of telecom operators and e-commerce, a large number of customer service personnel are required to handle a large number of business work orders. The transformation and optimization of the customer service business system through artificial intelligence technologies such as machine learning is important to impr...

AI Technical Summary

Problems solved by technology

Although the page information is divided into large categories, customer service personnel often need to use the mouse to call the information of multiple pages for verification in finer-grained business

There is a large amount of information redundancy in the way of multi-page verification, which leads to a decrease in the work efficiency of customer service personnel and a bad experience for customers

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