A Data Mining Method for Discovering Potential Telephone Replacement Users

Abstract

The invention provides a data mining method for finding potential telecommunication users changing cell phones. The data mining method comprises the following step of 1 the data set constructing stage and 2 the mining stage. The data set constructing stage comprises sub-steps of a, collecting consumption information of the users, historical information that the users change the cell phones, user information and terminal information; b, preprocessing data and generating data sets at the same time; c, processing the data sets in unbalanced categories and forming final training sets and prediction sets. The mining stage comprises the sub-steps of a, acquiring the data sets processed and generated in the step 1-c; b, finding the potential users changing the cell phones by implementing the decision tree algorithm; c, ending the stage. The potential users changing the cell phones are found in the telecommunication users based on the data mining technology. Compared with a traditional method, the data mining method is more accurate and efficient, and has the series of advantages of being easy to achieve, low in cost and the like.

Description

Technical field [0001] The invention relates to a method for constructing a data set, a method for solving the problem of unbalanced categories, and a technology for mining potential telecommunications users who are changing phones by using a decision tree algorithm on the data set. Background technique [0002] The use of data mining technology can intelligently analyze the data of telecommunication users and discover potential user switching rules. One type of application commonly used in data mining of potential telecom users is the decision tree classification algorithm, which predicts the user's future replacement behavior based on the user's consumption data and replacement information. The invention also uses the KNN algorithm and the clustering algorithm to perform under-sampling processing on the unbalanced category data, and constructs a data set with balanced and uniform data. At the same time, the information gain rate is used for attribute selection when data is pre...

AI Technical Summary

Problems solved by technology

[0004] The idea of ​​locating potential phone replacement users based on data mining breaks the convention of the phone replacement model based on traditional experience. Using the decision tree algorithm in data mining can dig deep into the information of user replacement, discover the characteristics of user replacement mobile phones and the characteristics of user replacement. The law of the machine overcomes the shortcomings of the traditional human experience summary that cannot be more targeted and highly accurate

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