System with network satisfaction degree estimation and early warning function and implementing method thereof
A satisfaction and network technology, applied in transmission systems, digital transmission systems, data exchange networks, etc., can solve problems such as inability to find, lag in satisfaction analysis, and inability to find dissatisfied customers, to achieve the effect of extraction
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Embodiment 1
[0041] Such as figure 1 The system with network satisfaction prediction and early warning function shown has an input terminal and an output terminal, and both the input terminal and the output terminal adopt the prior art. The system also includes a data input module 101, a data processing module 102, and a data splitting module 103. The predictive model generation module 104 and the predictive model output module 105, the data input module 101, the data processing module 102, the data splitting module 103, the predictive model generation module 104 and the predictive model output module 105 are connected in sequence, wherein,
[0042] The data input module 101 is used to collect system normal data and customer network satisfaction data input by the input terminal;
[0043] The data processing module 102 is used for receiving the data transmitted by the data input module 101, and merging, cleaning and processing the received data;
[0044]The data splitting module 103 is use...
Embodiment 2
[0069] Such as image 3 The system with network satisfaction prediction and early warning function shown is different from the first embodiment in that the system of this embodiment also includes a prediction model evaluation module 106, which is connected to the data splitting module 103 , receiving the data of the test set, which is used to compare the prediction result of the prediction model generation module 104 with the actual customer network satisfaction actual data obtained during the modeling period, so as to verify the authenticity and reliability of the model.
[0070] The accuracy of the predictive model is evaluated on a previously unused test data set, mainly measured in terms of error rate and lift. The error rate refers to the percentage of records that are misclassified, and a false positive matrix is often used to distinguish false positives from false negatives. The lift refers to the amount of change in the concentration of the specified group when the ...
Embodiment 3
[0077] Such as Figure 5 The shown system with network satisfaction prediction and early warning function is different from the second embodiment in that the system also includes a data analysis module 107, which is connected to the output terminal and is used to receive the output output from the output terminal. data and analyze the data.
[0078] The in-depth analysis of the data output from the output terminal includes sorting and generating a list of dissatisfied customers according to the value of customers and the possibility of dissatisfaction with the network in the future, grouping and describing the characteristics of dissatisfied customers, and utilizing the relationship between customers and network facilities. The mapping relationship maps unsatisfied customers in the future to facilities that may cause customer dissatisfaction, outputs a list of network facilities that need attention, and performs location-based clustering and feature analysis on network facilit...
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