# Research on the Prediction of Operator Users' Number Portability Based on Community Detection
###### Abstract  
In 2019, China introduced a policy on Number Portability Management, which has resulted in a rapid increase in the number of lost users among telecom companies. Telecom companies must urgently distinguish those with a tendency toward number portability. However, existing prediction research lacks the input of temporal variations in user data and the graph-based analysis of user relationship characteristics, resulting in a poor prediction effect. In this paper, a neural-network-based approach has been applied to address the limitation, whereby user data do not feature temporal variation. Furthermore, innovative approaches have been proposed to construct multilayer community networks through users' geographic attributes and to analyze community networks with a network embedding method based on the matrix factorization framework. This fills a gap in existing research areas, whereby the geographic attributes of users have not received much attention. Considering the extensive inputs and multiple features of the predicted attributes, in this paper, the strengths and weaknesses of three feature selection methods are compared, as well as the prediction accuracy of each of the five prediction models. Finally, the embedded feature selection method, deep neural network model, and the Light GBM model are shown to provide better results. After introducing the user community network, it was found that the prediction evaluation indicators of both the deep neural network model and the Light GBM model are improved. a _applied_  
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**Citation:** [PERSON]; [PERSON] Research on the Prediction of Operator Users' Number Portability Based on Community Detection. _Appl. Sci._  
**2023**, _13_, 3497. [[https://doi.org/10.3390/app13063497](https://doi.org/10.3390/app13063497)]([https://doi.org/10.3390/app13063497](https://doi.org/10.3390/app13063497))  
Academic Editors [PERSON] and [PERSON]  
Received: 16 February 2023  
Revised: 8 March 2023  
Revised: 9 March 2023  
Revised: 8 March 2023  
Revised: 9 March 2023  
had become increasingly fierce. Operators at the municipal level who have to manually confirm whether the current millions of users tend to switch their carriers are burdened with a huge workload and face higher inaccuracies. Thus, traditional predictive studies on users leaving the network (i.e., users permanently closing an existing phone number) fall behind the current demands of communication companies. Considering the late launches of policies related to number portability in China, research in the related field is low in quantity and is limited to discussions on policies themselves. A handful of articles adopted data mining for number portability research, while few scholars are equally familiar with telecommunications operator enterprises and data mining. This situation means it is more difficult to conduct a predictive study regarding number portability. Out of the four patents that have been applied in China [2; 3; 4; 5], only [PERSON] et al. considered the multi-month attribute data of users before numbers were ported. However, their processing method was limited to directly inputting a few specific user characteristics of the target users from a period of time before the current moment into the neural network model, without taking into account the changing trend of users' multi-month attribute analysis. [PERSON], [PERSON] et al. from the China Unicom Research Institute present a detailed integration solution for blockchain and mobile number portability [6]. Other research projects only utilized the attribute data of users for one month to predict portability. In addition, researchers have not fully grasped the key points that relate to users leaving a network. For example, previous studies did not pay attention to users' community attributes, and no one has attempted to apply graph theory to predict number portability. However, according to the work experience of the employees of the operators, the communities where customers live greatly affect the customers' ideas of number portability.